7 code implementations • 2 Nov 2018 • Hui Li, Peng Wang, Chunhua Shen, Guyu Zhang
Recognizing irregular text in natural scene images is challenging due to the large variance in text appearance, such as curvature, orientation and distortion.
Ranked #26 on Scene Text Recognition on ICDAR2015
3 code implementations • CVPR 2020 • Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, Yanning Zhang
The success of deep neural networks relies on significant architecture engineering.
Ranked #113 on Object Detection on COCO test-dev
2 code implementations • 28 Sep 2023 • Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, Tianhang Zhu
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans.
Ranked #3 on Multi-Label Text Classification on CC3M-TagMask
4 code implementations • 7 Feb 2022 • Peng Wang, An Yang, Rui Men, Junyang Lin, Shuai Bai, Zhikang Li, Jianxin Ma, Chang Zhou, Jingren Zhou, Hongxia Yang
In this work, we pursue a unified paradigm for multimodal pretraining to break the scaffolds of complex task/modality-specific customization.
Ranked #1 on Visual Question Answering on VQA v2 test-std (yes/no metric)
2 code implementations • 18 May 2023 • Peng Wang, Shijie Wang, Junyang Lin, Shuai Bai, Xiaohuan Zhou, Jingren Zhou, Xinggang Wang, Chang Zhou
In this work, we explore a scalable way for building a general representation model toward unlimited modalities.
Ranked #1 on Semantic Segmentation on ADE20K (using extra training data)
1 code implementation • 24 Aug 2023 • Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, Jingren Zhou
In this work, we introduce the Qwen-VL series, a set of large-scale vision-language models (LVLMs) designed to perceive and understand both texts and images.
Ranked #3 on Visual Question Answering on MM-Vet
1 code implementation • 10 Jan 2022 • Ningyu Zhang, Xin Xu, Liankuan Tao, Haiyang Yu, Hongbin Ye, Shuofei Qiao, Xin Xie, Xiang Chen, Zhoubo Li, Lei LI, Xiaozhuan Liang, Yunzhi Yao, Shumin Deng, Peng Wang, Wen Zhang, Zhenru Zhang, Chuanqi Tan, Qiang Chen, Feiyu Xiong, Fei Huang, Guozhou Zheng, Huajun Chen
We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base population.
4 code implementations • 28 Feb 2017 • Jonathan Protzenko, Jean-Karim Zinzindohoué, Aseem Rastogi, Tahina Ramananandro, Peng Wang, Santiago Zanella-Béguelin, Antoine Delignat-Lavaud, Catalin Hritcu, Karthikeyan Bhargavan, Cédric Fournet, Nikhil Swamy
Low* is a shallow embedding of a small, sequential, well-behaved subset of C in F*, a dependently-typed variant of ML aimed at program verification.
Programming Languages Cryptography and Security
1 code implementation • 4 Aug 2022 • Hao Yang, Junyang Lin, An Yang, Peng Wang, Chang Zhou, Hongxia Yang
Prompt tuning has become a new paradigm for model tuning and it has demonstrated success in natural language pretraining and even vision pretraining.
Ranked #2 on Visual Entailment on SNLI-VE test
1 code implementation • 19 Dec 2022 • Junyang Lin, Xuancheng Ren, Yichang Zhang, Gao Liu, Peng Wang, An Yang, Chang Zhou
This paper proposes a new method, OFA-OCR, to transfer multimodal pretrained models to text recognition.
6 code implementations • NeurIPS 2021 • Peng Wang, Lingjie Liu, YuAn Liu, Christian Theobalt, Taku Komura, Wenping Wang
In NeuS, we propose to represent a surface as the zero-level set of a signed distance function (SDF) and develop a new volume rendering method to train a neural SDF representation.
2 code implementations • CVPR 2019 • Zhao-Min Chen, Xiu-Shen Wei, Peng Wang, Yanwen Guo
The task of multi-label image recognition is to predict a set of object labels that present in an image.
Ranked #12 on Multi-Label Classification on PASCAL VOC 2007
3 code implementations • 22 May 2023 • Yunzhi Yao, Peng Wang, Bozhong Tian, Siyuan Cheng, Zhoubo Li, Shumin Deng, Huajun Chen, Ningyu Zhang
Our objective is to provide valuable insights into the effectiveness and feasibility of each editing technique, thereby assisting the community in making informed decisions on the selection of the most appropriate method for a specific task or context.
2 code implementations • 14 Aug 2023 • Peng Wang, Ningyu Zhang, Bozhong Tian, Zekun Xi, Yunzhi Yao, Ziwen Xu, Mengru Wang, Shengyu Mao, Xiaohan Wang, Siyuan Cheng, Kangwei Liu, Yuansheng Ni, Guozhou Zheng, Huajun Chen
Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to outdated/noisy data.
2 code implementations • 2 Jan 2024 • Ningyu Zhang, Yunzhi Yao, Bozhong Tian, Peng Wang, Shumin Deng, Mengru Wang, Zekun Xi, Shengyu Mao, Jintian Zhang, Yuansheng Ni, Siyuan Cheng, Ziwen Xu, Xin Xu, Jia-Chen Gu, Yong Jiang, Pengjun Xie, Fei Huang, Lei Liang, Zhiqiang Zhang, Xiaowei Zhu, Jun Zhou, Huajun Chen
In this paper, we first define the knowledge editing problem and then provide a comprehensive review of cutting-edge approaches.
Ranked #1 on knowledge editing on zsRE (using extra training data)
1 code implementation • ICLR 2022 • Jiatao Gu, Lingjie Liu, Peng Wang, Christian Theobalt
We perform volume rendering only to produce a low-resolution feature map and progressively apply upsampling in 2D to address the first issue.
2 code implementations • 8 Sep 2022 • Peng Wang, Cheng Da, Cong Yao
In this work, we first draw inspiration from the recent progress in Vision Transformer (ViT) to construct a conceptually simple yet powerful vision STR model, which is built upon ViT and outperforms previous state-of-the-art models for scene text recognition, including both pure vision models and language-augmented methods.
Ranked #1 on Scene Text Recognition on Uber-Text (using extra training data)
2 code implementations • 8 Sep 2022 • Cheng Da, Peng Wang, Cong Yao
A novel scene text recognizer based on Vision-Language Transformer (VLT) is presented.
1 code implementation • 25 Jul 2023 • Cheng Da, Peng Wang, Cong Yao
Specifically, MGP-STR achieves an average recognition accuracy of $94\%$ on standard benchmarks for scene text recognition.
1 code implementation • ICCV 2023 • Changxu Cheng, Peng Wang, Cheng Da, Qi Zheng, Cong Yao
The diversity in length constitutes a significant characteristic of text.
1 code implementation • 28 Mar 2023 • Peng Wang, YuAn Liu, Zhaoxi Chen, Lingjie Liu, Ziwei Liu, Taku Komura, Christian Theobalt, Wenping Wang
Based on our analysis, we further propose a novel space-warping method called perspective warping, which allows us to handle arbitrary trajectories in the grid-based NeRF framework.
2 code implementations • 31 Aug 2023 • Yichun Shi, Peng Wang, Jianglong Ye, Mai Long, Kejie Li, Xiao Yang
We introduce MVDream, a diffusion model that is able to generate consistent multi-view images from a given text prompt.
2 code implementations • 16 Mar 2018 • Xinyu Huang, Peng Wang, Xinjing Cheng, Dingfu Zhou, Qichuan Geng, Ruigang Yang
In this paper, we provide a sensor fusion scheme integrating camera videos, consumer-grade motion sensors (GPS/IMU), and a 3D semantic map in order to achieve robust self-localization and semantic segmentation for autonomous driving.
1 code implementation • 27 May 2023 • YuAn Liu, Peng Wang, Cheng Lin, Xiaoxiao Long, Jiepeng Wang, Lingjie Liu, Taku Komura, Wenping Wang
We present a neural rendering-based method called NeRO for reconstructing the geometry and the BRDF of reflective objects from multiview images captured in an unknown environment.
1 code implementation • ECCV 2018 • Xinjing Cheng, Peng Wang, Ruigang Yang
Depth estimation from a single image is a fundamental problem in computer vision.
1 code implementation • 4 Oct 2018 • Xinjing Cheng, Peng Wang, Ruigang Yang
In this paper, we propose a simple yet effective convolutional spatial propagation network (CSPN) to learn the affinity matrix for various depth estimation tasks.
1 code implementation • 20 Jul 2016 • Qi Wu, Damien Teney, Peng Wang, Chunhua Shen, Anthony Dick, Anton Van Den Hengel
Visual Question Answering (VQA) is a challenging task that has received increasing attention from both the computer vision and the natural language processing communities.
1 code implementation • NeurIPS 2023 • Shitao Tang, Fuyang Zhang, Jiacheng Chen, Peng Wang, Yasutaka Furukawa
This paper introduces MVDiffusion, a simple yet effective method for generating consistent multi-view images from text prompts given pixel-to-pixel correspondences (e. g., perspective crops from a panorama or multi-view images given depth maps and poses).
1 code implementation • CVPR 2022 • YuAn Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, Wenping Wang
On such a 3D point, these generalization methods will include inconsistent image features from invisible views, which interfere with the radiance field construction.
1 code implementation • 12 Jun 2022 • Xiaoxiao Long, Cheng Lin, Peng Wang, Taku Komura, Wenping Wang
We introduce SparseNeuS, a novel neural rendering based method for the task of surface reconstruction from multi-view images.
1 code implementation • CVPR 2020 • Shizhe Chen, Qin Jin, Peng Wang, Qi Wu
From the ASG, we propose a novel ASG2Caption model, which is able to recognise user intentions and semantics in the graph, and therefore generate desired captions according to the graph structure.
1 code implementation • 7 May 2020 • Peng Wang, Lingjie Liu, Nenglun Chen, Hung-Kuo Chu, Christian Theobalt, Wenping Wang
We propose the first approach that simultaneously estimates camera motion and reconstructs the geometry of complex 3D thin structures in high quality from a color video captured by a handheld camera.
1 code implementation • 24 Oct 2021 • Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen, Yanning Zhang
Neural Architecture Search (NAS) has shown great potential in effectively reducing manual effort in network design by automatically discovering optimal architectures.
1 code implementation • CVPR 2023 • Peng Wang, Lingzhe Zhao, Ruijie Ma, Peidong Liu
Our approach models the physical image formation process of a motion blurred image, and jointly learns the parameters of NeRF and recovers the camera motion trajectories during exposure time.
1 code implementation • 30 Dec 2019 • Ling Luo, Dingyu Xue, Xinglong Feng, Yichun Yu, Peng Wang
Modern approaches for semantic segmention usually pay too much attention to the accuracy of the model, and therefore it is strongly recommended to introduce cumbersome backbones, which brings heavy computation burden and memory footprint.
1 code implementation • 25 Oct 2023 • Guangcong Wang, Peng Wang, Zhaoxi Chen, Wenping Wang, Chen Change Loy, Ziwei Liu
In this paper, we present PERF, a 360-degree novel view synthesis framework that trains a panoramic neural radiance field from a single panorama.
1 code implementation • 8 Dec 2022 • Jinze Bai, Rui Men, Hao Yang, Xuancheng Ren, Kai Dang, Yichang Zhang, Xiaohuan Zhou, Peng Wang, Sinan Tan, An Yang, Zeyu Cui, Yu Han, Shuai Bai, Wenbin Ge, Jianxin Ma, Junyang Lin, Jingren Zhou, Chang Zhou
As a starting point, we provide presets of 7 different modalities and 23 highly-diverse example tasks in OFASys, with which we also develop a first-in-kind, single model, OFA+, that can handle text, image, speech, video, and motion data.
1 code implementation • CVPR 2021 • Mingyu Ding, Xiaochen Lian, Linjie Yang, Peng Wang, Xiaojie Jin, Zhiwu Lu, Ping Luo
Last, we proposed an efficient fine-grained search strategy to train HR-NAS, which effectively explores the search space, and finds optimal architectures given various tasks and computation resources.
1 code implementation • 8 Oct 2018 • Yang Wang, Zhenheng Yang, Peng Wang, Yi Yang, Chenxu Luo, Wei Xu
Then the whole scene is decomposed into moving foreground and static background by compar- ing the estimated optical flow and rigid flow derived from the depth and ego-motion.
1 code implementation • 1 Jan 2017 • Jiaming Xu, Peng Wang, Suncong Zheng, Guanhua Tian, Jun Zhao, Bo Xu
Short text clustering is a challenging problem due to its sparseness of text representation.
Ranked #2 on Short Text Clustering on Stackoverflow
1 code implementation • 10 Dec 2021 • Chaochen Gao, Xing Wu, Peng Wang, Jue Wang, Liangjun Zang, Zhongyuan Wang, Songlin Hu
To tackle that, we propose an effective knowledge distillation framework for contrastive sentence embeddings, termed DistilCSE.
1 code implementation • 17 Jul 2020 • Miao Liao, Sibo Zhang, Peng Wang, Hao Zhu, Xinxin Zuo, Ruigang Yang
In this paper, we propose a novel approach to convert given speech audio to a photo-realistic speaking video of a specific person, where the output video has synchronized, realistic, and expressive rich body dynamics.
1 code implementation • CVPR 2020 • Jie Li, Kai Han, Peng Wang, Yu Liu, Xia Yuan
In contrast to the standard 3D convolution that is limited to a fixed 3D receptive field, our module is capable of modeling the dimensional anisotropy voxel-wisely.
1 code implementation • 18 Mar 2024 • Lingzhe Zhao, Peng Wang, Peidong Liu
In this paper, we introduce a novel approach, named BAD-Gaussians (Bundle Adjusted Deblur Gaussian Splatting), which leverages explicit Gaussian representation and handles severe motion-blurred images with inaccurate camera poses to achieve high-quality scene reconstruction.
1 code implementation • 2 Jun 2020 • Peng Wang, Dongyang Liu, Hui Li, Qi Wu
In this case, we need to use commonsense knowledge to identify the objects in the image.
1 code implementation • CVPR 2018 • Zhenheng Yang, Peng Wang, Yang Wang, Wei Xu, Ram Nevatia
In our framework, the predicted depths, normals and edges are forced to be consistent all the time.
1 code implementation • 16 Dec 2016 • Rui Zhao, Ruqiang Yan, Zhenghua Chen, Kezhi Mao, Peng Wang, Robert X. Gao
Since 2006, deep learning (DL) has become a rapidly growing research direction, redefining state-of-the-art performances in a wide range of areas such as object recognition, image segmentation, speech recognition and machine translation.
1 code implementation • 6 Sep 2019 • Jinghao Zhou, Peng Wang, Haoyang Sun
The problem of visual object tracking has traditionally been handled by variant tracking paradigms, either learning a model of the object's appearance exclusively online or matching the object with the target in an offline-trained embedding space.
1 code implementation • 31 Aug 2023 • Shuai Bai, Shusheng Yang, Jinze Bai, Peng Wang, Xingxuan Zhang, Junyang Lin, Xinggang Wang, Chang Zhou, Jingren Zhou
Large vision-language models (LVLMs) have recently witnessed rapid advancements, exhibiting a remarkable capacity for perceiving, understanding, and processing visual information by connecting visual receptor with large language models (LLMs).
1 code implementation • 22 Aug 2023 • Peng Wu, Xuerong Zhou, Guansong Pang, Lingru Zhou, Qingsen Yan, Peng Wang, Yanning Zhang
With the benefit of dual branch, VadCLIP achieves both coarse-grained and fine-grained video anomaly detection by transferring pre-trained knowledge from CLIP to WSVAD task.
1 code implementation • 9 Dec 2020 • Qi Zhu, Chenyu Gao, Peng Wang, Qi Wu
Texts appearing in daily scenes that can be recognized by OCR (Optical Character Recognition) tools contain significant information, such as street name, product brand and prices.
1 code implementation • CVPR 2018 • Peng Wang, Ruigang Yang, Binbin Cao, Wei Xu, Yuanqing Lin
The uniqueness of our design is a sensor fusion scheme which integrates camera videos, motion sensors (GPS/IMU), and a 3D semantic map in order to achieve robustness and efficiency of the system.
1 code implementation • CVPR 2022 • Jingzhou Chen, Peng Wang, Jian Liu, Yuntao Qian
Hierarchical multi-granularity classification (HMC) assigns hierarchical multi-granularity labels to each object and focuses on encoding the label hierarchy, e. g., ["Albatross", "Laysan Albatross"] from coarse-to-fine levels.
1 code implementation • 14 Jan 2022 • Peng Wang, Xin Xie, Xiaohan Wang, Ningyu Zhang
Previous knowledge graph embedding approaches usually map entities to representations and utilize score functions to predict the target entities, yet they typically struggle to reason rare or emerging unseen entities.
Ranked #1 on Link Prediction on FB15k-237-ind
1 code implementation • 16 Nov 2020 • Hiroaki Hayashi, Prashant Budania, Peng Wang, Chris Ackerson, Raj Neervannan, Graham Neubig
In this paper, we propose WikiAsp, a large-scale dataset for multi-domain aspect-based summarization that attempts to spur research in the direction of open-domain aspect-based summarization.
1 code implementation • 11 Feb 2024 • Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi
Large language models (LLMs) like ChatGPT, exhibit powerful zero-shot and instruction-following capabilities, have catalyzed a revolutionary transformation across diverse fields, especially for open-ended tasks.
1 code implementation • 30 May 2022 • Angtian Wang, Peng Wang, Jian Sun, Adam Kortylewski, Alan Yuille
The Gaussian reconstruction kernels have been proposed by Westover (1990) and studied by the computer graphics community back in the 90s, which gives an alternative representation of object 3D geometry from meshes and point clouds.
1 code implementation • 30 Mar 2017 • Alireza Fathi, Zbigniew Wojna, Vivek Rathod, Peng Wang, Hyun Oh Song, Sergio Guadarrama, Kevin P. Murphy
We propose a new method for semantic instance segmentation, by first computing how likely two pixels are to belong to the same object, and then by grouping similar pixels together.
1 code implementation • CVPR 2023 • Haoyu Wang, Guansong Pang, Peng Wang, Lei Zhang, Wei Wei, Yanning Zhang
Few-shot open-set recognition (FSOR) is a challenging task of great practical value.
1 code implementation • CVPR 2022 • Fushun Zhu, Shan Zhao, Peng Wang, Hao Wang, Hua Yan, Shuaicheng Liu
We propose a semi-supervised network for wide-angle portraits correction.
1 code implementation • 17 Aug 2022 • Yinghui Xing, Qirui Wu, De Cheng, Shizhou Zhang, Guoqiang Liang, Peng Wang, Yanning Zhang
To make the final image feature concentrate more on the target visual concept, a Class-Aware Visual Prompt Tuning (CAVPT) scheme is further proposed in our DPT, where the class-aware visual prompt is generated dynamically by performing the cross attention between text prompts features and image patch token embeddings to encode both the downstream task-related information and visual instance information.
1 code implementation • ICCV 2023 • Shubo Liu, Hongsheng Zhang, Yuankai Qi, Peng Wang, Yaning Zhang, Qi Wu
Navigating in the sky is more complicated than on the ground because agents need to consider the flying height and more complex spatial relationship reasoning.
1 code implementation • 14 Oct 2018 • Chenxu Luo, Zhenheng Yang, Peng Wang, Yang Wang, Wei Xu, Ram Nevatia, Alan Yuille
Performance on the five tasks of depth estimation, optical flow estimation, odometry, moving object segmentation and scene flow estimation shows that our approach outperforms other SoTA methods.
1 code implementation • CVPR 2022 • Xueqing Deng, Peng Wang, Xiaochen Lian, Shawn Newsam
Notably, NightLab contains models at two levels of granularity, i. e. image and regional, and each level is composed of light adaptation and segmentation modules.
1 code implementation • CVPR 2022 • Wei Dong, Junsheng Wu, Yi Luo, ZongYuan Ge, Peng Wang
In this work, we present a simple-yet-effective self-supervised node representation learning strategy via directly maximizing the mutual information between the hidden representations of nodes and their neighbourhood, which can be theoretically justified by its link to graph smoothing.
1 code implementation • CVPR 2022 • Caiyuan Zheng, Hui Li, Seon-Min Rhee, Seungju Han, Jae-Joon Han, Peng Wang
A robust consistency regularization based semi-supervised framework is proposed for STR, which can effectively solve the instability issue due to domain inconsistency between synthetic and real images.
1 code implementation • 9 Feb 2023 • Wei Dong, Dawei Yan, Peng Wang
Considering the excessive memory overheads of contrastive learning, we further propose a negative-free solution, where the main contribution is a Graph Signal Decorrelation (GSD) constraint to avoid representation collapse and over-smoothing.
1 code implementation • 20 Aug 2023 • Zeyu Han, YuHan Wang, Luping Zhou, Peng Wang, Binyu Yan, Jiliu Zhou, Yan Wang, Dinggang Shen
To obtain high-quality positron emission tomography (PET) scans while reducing radiation exposure to the human body, various approaches have been proposed to reconstruct standard-dose PET (SPET) images from low-dose PET (LPET) images.
1 code implementation • CVPR 2022 • Yanyuan Qiao, Yuankai Qi, Yicong Hong, Zheng Yu, Peng Wang, Qi Wu
Pre-training has been adopted in a few of recent works for Vision-and-Language Navigation (VLN).
Ranked #4 on Visual Navigation on R2R
1 code implementation • NeurIPS 2023 • Wei Dong, Dawei Yan, Zhijun Lin, Peng Wang
Consequently, effectively adapting large pre-trained models to downstream tasks in an efficient manner has become a prominent research area.
1 code implementation • 5 May 2022 • Guozheng Li, Xu Chen, Peng Wang, Jiafeng Xie, Qiqing Luo
Recent work for extracting relations from texts has achieved excellent performance.
1 code implementation • 20 Apr 2023 • Yongming Yang, Shuwei Shao, Tao Yang, Peng Wang, Zhuo Yang, Chengdong Wu, Hao liu
To address this issue, we introduce a gradient loss to penalize edge fluctuations ambiguous around stepped edge structures and a normal loss to explicitly express the sensitivity to frequently small structures, and propose a geometric consistency loss to spreads the spatial information across the sample grids to constrain the global geometric anatomy structures.
1 code implementation • CVPR 2023 • Fei Zhou, Peng Wang, Lei Zhang, Wei Wei, Yanning Zhang
Prototypical Network is a popular few-shot solver that aims at establishing a feature metric generalizable to novel few-shot classification (FSC) tasks using deep neural networks.
1 code implementation • 15 Dec 2020 • Feixiang Lu, Zongdai Liu, Hui Miao, Peng Wang, Liangjun Zhang, Ruigang Yang, Dinesh Manocha, Bin Zhou
For autonomous driving, the dynamics and states of vehicle parts such as doors, the trunk, and the bonnet can provide meaningful semantic information and interaction states, which are essential to ensuring the safety of the self-driving vehicle.
1 code implementation • ECCV 2022 2022 • Wei Suo, Mengyang Sun, Kai Niu, Yiqi Gao, Peng Wang, Yanning Zhang, Qi Wu
Text-based person search aims to associate pedestrian images with natural language descriptions.
Ranked #8 on Text based Person Retrieval on ICFG-PEDES
1 code implementation • 9 May 2018 • Yuhang Song, Chao Yang, Yeji Shen, Peng Wang, Qin Huang, C. -C. Jay Kuo
In this paper, we focus on image inpainting task, aiming at recovering the missing area of an incomplete image given the context information.
2 code implementations • 7 Dec 2020 • Haokui Zhang, Ying Li, Yenan Jiang, Peng Wang, Qiang Shen, Chunhua Shen
In contrast to previous approaches, we do not impose restrictions over the source data sets, in which they do not have to be collected by the same sensors as the target data sets.
2 code implementations • 14 Feb 2019 • Peng Wang, Hong Xu, Xin Jin, Tao Wang
Mice payments are directly sent by looking up a routing table with a few precomputed paths to reduce probing overhead.
Networking and Internet Architecture
1 code implementation • 14 Aug 2019 • Shizhou Zhang, Qi Zhang, Yifei Yang, Xing Wei, Peng Wang, Bingliang Jiao, Yanning Zhang
Our method can learn a discriminative and compact feature representation for ReID in aerial imagery and can be trained in an end-to-end fashion efficiently.
1 code implementation • 15 May 2023 • Yunzhi Yao, Peng Wang, Shengyu Mao, Chuanqi Tan, Fei Huang, Huajun Chen, Ningyu Zhang
Previous studies have revealed that vanilla pre-trained language models (PLMs) lack the capacity to handle knowledge-intensive NLP tasks alone; thus, several works have attempted to integrate external knowledge into PLMs.
1 code implementation • 1 Jul 2021 • Shuaicheng Niu, Jiaxiang Wu, Guanghui Xu, Yifan Zhang, Yong Guo, Peilin Zhao, Peng Wang, Mingkui Tan
To address this, we present a neural architecture adaptation method, namely Adaptation eXpert (AdaXpert), to efficiently adjust previous architectures on the growing data.
1 code implementation • SIGMOD/PODS 2022 • Jianhong Tu, Ju Fan, Nan Tang, Peng Wang, Chengliang Chai, Guoliang Li, Ruixue Fan, Xiaoyong Du
Entity resolution (ER) is a core problem of data integration.
Ranked #2 on Entity Resolution on WDC Watches-small
1 code implementation • CVPR 2023 • Qingsheng Wang, Lingqiao Liu, Chenchen Jing, Hao Chen, Guoqiang Liang, Peng Wang, Chunhua Shen
Compositional Zero-Shot Learning (CZSL) aims to train models to recognize novel compositional concepts based on learned concepts such as attribute-object combinations.
Ranked #1 on Compositional Zero-Shot Learning on MIT-States
1 code implementation • SIGMOD/PODS 2023 • Jianhong Tu, Ju Fan, Nan Tang, Peng Wang, Guoliang Li, Xiaoyong Du, Xiaofeng Jia, Song Gao
The widely used practice is to build task-specific or even dataset-specific solutions, which are hard to generalize and disable the opportunities of knowledge sharing that can be learned from different datasets and multiple tasks.
1 code implementation • 18 Feb 2019 • Youngjoo Kim, Peng Wang, Lyudmila Mihaylova
We use a graph of a vehicular road network with recurrent neural networks (RNNs) to infer the interaction between adjacent road segments as well as the temporal dynamics.
1 code implementation • 3 Mar 2021 • Youngjoo Kim, Peng Wang, Lyudmila Mihaylova
With the real traffic speed data measured in the city of Santander, we demonstrate the proposed SRNN outperforms the image-based approaches using the capsule network (CapsNet) by 14. 1% and the convolutional neural network (CNN) by 5. 87%, respectively, in terms of root mean squared error (RMSE).
2 code implementations • 1 Jun 2020 • Chenyu Gao, Qi Zhu, Peng Wang, Hui Li, Yuliang Liu, Anton Van Den Hengel, Qi Wu
In this paper, we propose an end-to-end structured multimodal attention (SMA) neural network to mainly solve the first two issues above.
1 code implementation • 4 Oct 2023 • Moyang Li, Peng Wang, Lingzhe Zhao, Bangyan Liao, Peidong Liu
USB-NeRF is able to correct rolling shutter distortions and recover accurate camera motion trajectory simultaneously under the framework of NeRF, by modeling the physical image formation process of a RS camera.
1 code implementation • 2 Apr 2019 • Lu Yang, Fan Dang, Peng Wang, Hui Li, Zhen Li, Yanning Zhang
In this work, we propose a simple yet strong approach for scene text recognition.
1 code implementation • 24 Aug 2023 • Shizhou Zhang, Qingchun Yang, De Cheng, Yinghui Xing, Guoqiang Liang, Peng Wang, Yanning Zhang
In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named G2APS, which contains 31, 770 images of 260, 559 annotated bounding boxes for 2, 644 identities appearing in both of the UAVs and ground surveillance cameras.
1 code implementation • 28 Mar 2024 • Wei Dong, Xing Zhang, Bihui Chen, Dawei Yan, Zhijun Lin, Qingsen Yan, Peng Wang, Yang Yang
Parameter-efficient fine-tuning for pre-trained Vision Transformers aims to adeptly tailor a model to downstream tasks by learning a minimal set of new adaptation parameters while preserving the frozen majority of pre-trained parameters.
1 code implementation • 11 Nov 2023 • Peng Wang, Haiming Yao, Wenyong Yu
Current unsupervised models struggle to strike a balance between detecting texture and object defects, lacking the capacity to discern latent representations and intricate features.
1 code implementation • 23 Jul 2018 • Youngjoo Kim, Peng Wang, Yifei Zhu, Lyudmila Mihaylova
Traffic flow data from induction loop sensors are essentially a time series, which is also spatially related to traffic in different road segments.
1 code implementation • 28 Nov 2019 • Rong Zhang, Wei Li, Peng Wang, Chenye Guan, Jin Fang, Yuhang Song, Jinhui Yu, Baoquan Chen, Weiwei Xu, Ruigang Yang
To deal with shadows, we build up an autonomous driving shadow dataset and design a deep neural network to detect shadows automatically.
1 code implementation • Findings (NAACL) 2022 • Zhen Zhang, Wei Zhu, Jinfan Zhang, Peng Wang, Rize Jin, Tae-Sun Chung
In this work, we propose Patient and Confident Early Exiting BERT (PCEE-BERT), an off-the-shelf sample-dependent early exiting method that can work with different PLMs and can also work along with popular model compression methods.
1 code implementation • 1 Jun 2023 • Can Yaras, Peng Wang, Wei Hu, Zhihui Zhu, Laura Balzano, Qing Qu
Second, it allows us to better understand deep representation learning by elucidating the linear progressive separation and concentration of representations from shallow to deep layers.
1 code implementation • 11 May 2018 • Xiu-Shen Wei, Peng Wang, Lingqiao Liu, Chunhua Shen, Jianxin Wu
To solve this problem, we propose an end-to-end trainable deep network which is inspired by the state-of-the-art fine-grained recognition model and is tailored for the FSFG task.
1 code implementation • 24 Jul 2023 • Peng Wu, Jing Liu, Xiangteng He, Yuxin Peng, Peng Wang, Yanning Zhang
In this context, we propose a novel task called Video Anomaly Retrieval (VAR), which aims to pragmatically retrieve relevant anomalous videos by cross-modalities, e. g., language descriptions and synchronous audios.
2 code implementations • 19 Nov 2014 • Peng Wang, Baowen Xu, Yurong Wu, Xiaoyu Zhou
Finally, some future challenges of the link prediction in social networks are discussed.
Social and Information Networks Physics and Society
1 code implementation • 15 Mar 2024 • Yukun Li, Guansong Pang, Wei Suo, Chenchen Jing, Yuling Xi, Lingqiao Liu, Hao Chen, Guoqiang Liang, Peng Wang
Large pre-trained VLMs like CLIP have demonstrated superior zero-shot recognition ability, and a number of recent studies leverage this ability to mitigate catastrophic forgetting in CL, but they focus on closed-set CL in a single domain dataset.
1 code implementation • 19 Sep 2022 • Can Yaras, Peng Wang, Zhihui Zhu, Laura Balzano, Qing Qu
When training overparameterized deep networks for classification tasks, it has been widely observed that the learned features exhibit a so-called "neural collapse" phenomenon.
1 code implementation • 19 Jul 2023 • Feiran Hu, Peng Wang, Yangyang Li, Chenlong Duan, Zijian Zhu, Fei Wang, Faen Zhang, Yong Li, Xiu-Shen Wei
The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata.
1 code implementation • 6 Nov 2023 • Peng Wang, Xiao Li, Can Yaras, Zhihui Zhu, Laura Balzano, Wei Hu, Qing Qu
To the best of our knowledge, this is the first quantitative characterization of feature evolution in hierarchical representations of deep linear networks.
1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2021 • ZhaoMin Chen, Xiu-Shen Wei, Peng Wang, Yanwen Guo
The task of multi-label image recognition is to predict a set of object labels that present in an image.
Multi-Label Classification Multi-label Image Recognition with Partial Labels
1 code implementation • 11 Jun 2022 • Peng Wang, Huikang Liu, Anthony Man-Cho So, Laura Balzano
The K-subspaces (KSS) method is a generalization of the K-means method for subspace clustering.
1 code implementation • 21 Nov 2023 • Xiu-Shen Wei, Yang shen, Xuhao Sun, Peng Wang, Yuxin Peng
Our work focuses on tackling large-scale fine-grained image retrieval as ranking the images depicting the concept of interests (i. e., the same sub-category labels) highest based on the fine-grained details in the query.
1 code implementation • 25 Nov 2023 • Heng Tao Shen, Cheng Chen, Peng Wang, Lianli Gao, Meng Wang, Jingkuan Song
In this paper, we propose Continual Referring Expression Comprehension (CREC), a new setting for REC, where a model is learning on a stream of incoming tasks.
no code implementations • 5 Jun 2018 • Lei Zhang, Peng Wang, Chunhua Shen, Lingqiao Liu, Wei Wei, Yanning Zhang, Anton Van Den Hengel
In this study, we revisit this problem from an orthog- onal view, and propose a novel learning strategy to maxi- mize the pixel-wise fitting capacity of a given lightweight network architecture.
no code implementations • 17 Apr 2018 • Jiaolong Xu, Peng Wang, Heng Yang, Antonio M. López
Autonomous driving has harsh requirements of small model size and energy efficiency, in order to enable the embedded system to achieve real-time on-board object detection.
no code implementations • CVPR 2018 • Hao Zhu, Hao Su, Peng Wang, Xun Cao, Ruigang Yang
We study how to synthesize novel views of human body from a single image.
no code implementations • CVPR 2018 • Yang Wang, Yi Yang, Zhenheng Yang, Liang Zhao, Peng Wang, Wei Xu
Especially on KITTI dataset where abundant unlabeled samples exist, our unsupervised method outperforms its counterpart trained with supervised learning.
no code implementations • CVPR 2018 • Chao Ma, Chunhua Shen, Anthony Dick, Qi Wu, Peng Wang, Anton Van Den Hengel, Ian Reid
In this paper, we exploit a memory-augmented neural network to predict accurate answers to visual questions, even when those answers occur rarely in the training set.
no code implementations • CVPR 2018 • Liang-Chieh Chen, Alexander Hermans, George Papandreou, Florian Schroff, Peng Wang, Hartwig Adam
Within each region of interest, MaskLab performs foreground/background segmentation by combining semantic and direction prediction.
Ranked #85 on Instance Segmentation on COCO test-dev (using extra training data)
no code implementations • 27 Oct 2017 • Rong Kang, Chen Wang, Peng Wang, Yuting Ding, Jian-Min Wang
Hence, we formulate a new problem, called "fine-grained pattern matching", which allows users to specify varied granularities of matching deviation to different segments of a given pattern, and fuzzy regions for adaptive breakpoints determination between consecutive segments.
no code implementations • CVPR 2018 • Qi Wu, Peng Wang, Chunhua Shen, Ian Reid, Anton Van Den Hengel
The Visual Dialogue task requires an agent to engage in a conversation about an image with a human.
Ranked #4 on Visual Dialog on VisDial v0.9 val
no code implementations • 10 Nov 2017 • Zhenheng Yang, Peng Wang, Wei Xu, Liang Zhao, Ramakant Nevatia
Learning to reconstruct depths in a single image by watching unlabeled videos via deep convolutional network (DCN) is attracting significant attention in recent years.
no code implementations • 26 Sep 2017 • Hui Li, Peng Wang, Chunhua Shen
In contrast to existing approaches which take license plate detection and recognition as two separate tasks and settle them step by step, our method jointly solves these two tasks by a single network.
no code implementations • CVPR 2017 • Fangting Xia, Peng Wang, Xianjie Chen, Alan Yuille
To refine part segments, the refined pose and the original part potential are integrated through a Part FCN, where the skeleton feature from pose serves as additional regularization cues for part segments.
Ranked #5 on Human Part Segmentation on PASCAL-Part
no code implementations • 17 Jun 2016 • Peng Wang, Qi Wu, Chunhua Shen, Anton Van Den Hengel, Anthony Dick
We evaluate several baseline models on the FVQA dataset, and describe a novel model which is capable of reasoning about an image on the basis of supporting facts.
Ranked #2 on Visual Question Answering (VQA) on F-VQA
no code implementations • ICCV 2017 • Hui Li, Peng Wang, Chunhua Shen
In this work, we jointly address the problem of text detection and recognition in natural scene images based on convolutional recurrent neural networks.
no code implementations • 2 Feb 2017 • Xuanyang Xi, Yongkang Luo, Fengfu Li, Peng Wang, Hong Qiao
In this paper, we tackle this problem by proposing a fast and compact saliency score regression network which employs fully convolutional network, a special deep convolutional neural network, to estimate the saliency of objects in images.
1 code implementation • 16 Jan 2016 • Lingqiao Liu, Peng Wang, Chunhua Shen, Lei Wang, Anton Van Den Hengel, Chao Wang, Heng Tao Shen
To handle this limitation, in this paper we break the convention which assumes that a local feature is drawn from one of few Gaussian distributions.
no code implementations • 9 Mar 2016 • Qi Wu, Chunhua Shen, Anton Van Den Hengel, Peng Wang, Anthony Dick
Much recent progress in Vision-to-Language problems has been achieved through a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).
no code implementations • CVPR 2017 • Peng Wang, Qi Wu, Chunhua Shen, Anton Van Den Hengel
To train a method to perform even one of these operations accurately from {image, question, answer} tuples would be challenging, but to aim to achieve them all with a limited set of such training data seems ambitious at best.
no code implementations • 1 Aug 2016 • ZongYuan Ge, Chris McCool, Conrad Sanderson, Peng Wang, Lingqiao Liu, Ian Reid, Peter Corke
Fine-grained classification is a relatively new field that has concentrated on using information from a single image, while ignoring the enormous potential of using video data to improve classification.
no code implementations • 20 Nov 2015 • Peng Wang, Alan Yuille
In this paper we propose a deep network architecture, called DOC, which acts on a single image, detects object boundaries and estimates the border ownership (i. e. which side of the boundary is foreground and which is background).
no code implementations • 22 Jun 2016 • Jiewei Cao, Lingqiao Liu, Peng Wang, Zi Huang, Chunhua Shen, Heng Tao Shen
Instance retrieval requires one to search for images that contain a particular object within a large corpus.
no code implementations • 15 Mar 2016 • Qichang Hu, Peng Wang, Chunhua Shen, Anton Van Den Hengel, Fatih Porikli
In this work, we show that by re-using the convolutional feature maps (CFMs) of a deep convolutional neural network (DCNN) model as image features to train an ensemble of boosted decision models, we are able to achieve the best reported accuracy without using specially designed learning algorithms.
no code implementations • 27 Nov 2014 • Peng Wang, Chunhua Shen, Anton Van Den Hengel, Philip H. S. Torr
Two standard relaxation methods are widely used for solving general BQPs--spectral methods and semidefinite programming (SDP), each with their own advantages and disadvantages.
no code implementations • CVPR 2016 • Qi Wu, Peng Wang, Chunhua Shen, Anthony Dick, Anton Van Den Hengel
Priming a recurrent neural network with this combined information, and the submitted question, leads to a very flexible visual question answering approach.
no code implementations • 21 Nov 2015 • Fangting Xia, Peng Wang, Liang-Chieh Chen, Alan L. Yuille
To tackle these difficulties, we propose a "Hierarchical Auto-Zoom Net" (HAZN) for object part parsing which adapts to the local scales of objects and parts.
Ranked #8 on Human Part Segmentation on PASCAL-Part
no code implementations • 14 Feb 2016 • Peng Wang, Lingqiao Liu, Chunhua Shen, Anton Van Den Hengel, Heng Tao Shen
To address this problem, we propose a novel approach by inspecting the distribution of the detection scores at multiple image regions based on the detector trained from the "regular object" and "other objects".
no code implementations • 31 Jan 2016 • Peng Wang, Lingqiao Liu, Chunhua Shen, Heng Tao Shen
Most video based action recognition approaches create the video-level representation by temporally pooling the features extracted at each frame.
no code implementations • 17 Aug 2015 • Fangting Xia, Jun Zhu, Peng Wang, Alan Yuille
Parsing human body into semantic regions is crucial to human-centric analysis.
no code implementations • 9 Nov 2015 • Peng Wang, Qi Wu, Chunhua Shen, Anton Van Den Hengel, Anthony Dick
We describe a method for visual question answering which is capable of reasoning about contents of an image on the basis of information extracted from a large-scale knowledge base.
no code implementations • 20 Apr 2014 • Peng Wang, Chunhua Shen, Anton Van Den Hengel, Philip Torr
We propose a Branch-and-Cut (B&C) method for solving general MAP-MRF inference problems.
no code implementations • 3 Jun 2015 • Tianyi Liu, Shuangsang Fang, Yuehui Zhao, Peng Wang, Jun Zhang
Deep learning refers to the shining branch of machine learning that is based on learning levels of representations.
no code implementations • ICCV 2015 • Peng Wang, Xiaohui Shen, Zhe Lin, Scott Cohen, Brian Price, Alan Yuille
Segmenting semantic objects from images and parsing them into their respective semantic parts are fundamental steps towards detailed object understanding in computer vision.
no code implementations • 4 Mar 2015 • Peng Wang, Yuanzhouhan Cao, Chunhua Shen, Lingqiao Liu, Heng Tao Shen
One challenge is that video contains a varying number of frames which is incompatible to the standard input format of CNNs.
no code implementations • CVPR 2015 • Peng Wang, Chunhua Shen, Anton Van Den Hengel
Conditional Random Fields (CRF) have been widely used in a variety of computer vision tasks.
1 code implementation • CVPR 2013 • Peng Wang, Chunhua Shen, Anton Van Den Hengel
Second, compared with conventional SDP methods, the new SDP formulation leads to a significantly more efficient and scalable dual optimization approach, which has the same degree of complexity as spectral methods.
no code implementations • 27 Jun 2018 • Zhenheng Yang, Peng Wang, Yang Wang, Wei Xu, Ram Nevatia
The four types of information, i. e. 2D flow, camera pose, segment mask and depth maps, are integrated into a differentiable holistic 3D motion parser (HMP), where per-pixel 3D motion for rigid background and moving objects are recovered.
no code implementations • 30 Aug 2018 • Lei Zhang, Peng Wang, Lingqiao Liu, Chunhua Shen, Wei Wei, Yannning Zhang, Anton Van Den Hengel
Towards this goal, we present a simple but effective two-branch network to simultaneously map semantic descriptions and visual samples into a joint space, on which visual embeddings are forced to regress to their class-level semantic embeddings and the embeddings crossing classes are required to be distinguishable by a trainable classifier.
no code implementations • 24 Nov 2018 • Haokui Zhang, Ying Li, Peng Wang, Yu Liu, Chunhua Shen
Different from RGB videos, depth data in RGB-D videos provide key complementary information for tristimulus visual data which potentially could achieve accuracy improvement for action recognition.
no code implementations • CVPR 2019 • Xibin Song, Peng Wang, Dingfu Zhou, Rui Zhu, Chenye Guan, Yuchao Dai, Hao Su, Hongdong Li, Ruigang Yang
Specifically, we first segment each car with a pre-trained Mask R-CNN, and then regress towards its 3D pose and shape based on a deformable 3D car model with or without using semantic keypoints.
no code implementations • CVPR 2019 • Hui Li, Peng Wang, Chunhua Shen, Anton Van Den Hengel
In contrast to struggling on multimodal feature fusion, in this paper, we propose to unify all the input information by natural language so as to convert VQA into a machine reading comprehension problem.
no code implementations • CVPR 2019 • Peng Wang, Qi Wu, Jiewei Cao, Chunhua Shen, Lianli Gao, Anton Van Den Hengel
Being composed of node attention component and edge attention component, the proposed graph attention mechanism explicitly represents inter-object relationships, and properties with a flexibility and power impossible with competing approaches.
no code implementations • IJCNLP 2017 • Xi-An Li, Peng Wang, Suixue Wang, Guanyu Jiang, Tianyuan You
Grammatical error diagnosis is an important task in natural language processing.
no code implementations • NeurIPS 2016 • Peng Wang, Xiaohui Shen, Bryan Russell, Scott Cohen, Brian Price, Alan L. Yuille
This paper introduces an approach to regularize 2. 5D surface normal and depth predictions at each pixel given a single input image.
no code implementations • 22 Jan 2019 • Xiu-Shen Wei, Quan Cui, Lei Yang, Peng Wang, Lingqiao Liu
The main challenge of this problem comes from the large scale and the fine-grained nature of the product categories as well as the difficulty for collecting training images that reflect the realistic checkout scenarios due to continuous update of the products.
no code implementations • CVPR 2013 • Peng Wang, Jingdong Wang, Gang Zeng, Weiwei Xu, Hongbin Zha, Shipeng Li
In visual recognition tasks, the design of low level image feature representation is fundamental.
no code implementations • CVPR 2015 • Peng Wang, Xiaohui Shen, Zhe Lin, Scott Cohen, Brian Price, Alan L. Yuille
By allowing for interactions between the depth and semantic information, the joint network provides more accurate depth prediction than a state-of-the-art CNN trained solely for depth prediction [5].
no code implementations • CVPR 2016 • Peng Wang, Lingqiao Liu, Chunhua Shen, Zi Huang, Anton Van Den Hengel, Heng Tao Shen
The key observation motivating our approach is that "regular object" images, "unusual object" images and "other objects" images exhibit different region-level scores in terms of both the score values and the spatial distributions.
no code implementations • CVPR 2017 • Peng Wang, Lingqiao Liu, Chunhua Shen, Zi Huang, Anton Van Den Hengel, Heng Tao Shen
One-shot learning is a challenging problem where the aim is to recognize a class identified by a single training image.
no code implementations • 24 Mar 2019 • Lei Zhang, Zhiqiang Lang, Peng Wang, Wei Wei, Shengcai Liao, Ling Shao, Yanning Zhang
To address this problem, we propose a pixel-aware deep function-mixture network for SSR, which is composed of a new class of modules, termed function-mixture (FM) blocks.
no code implementations • ICCV 2019 • Peng Wang, Bingliang Jiao, Lu Yang, Yifei Yang, Shizhou Zhang, Wei Wei, Yanning Zhang
It is capable of explicitly detecting discriminative parts for each specific vehicle and significantly outperforms the evaluated baselines and state-of-the-art vehicle ReID approaches.
no code implementations • 14 Jun 2019 • Peng Wang, Hui Li, Chunhua Shen
Text spotting in natural scene images is of great importance for many image understanding tasks.
no code implementations • 29 Jun 2019 • Jiaqi Yang, Siwen Quan, Peng Wang, Yanning Zhang
The outcomes present interesting findings that may shed new light on this community and provide complementary perspectives to existing evaluations on the topic of local geometric feature description.
no code implementations • 5 Jul 2019 • Jiaqi Yang, Ke Xian, Peng Wang, Yanning Zhang
Seeking consistent point-to-point correspondences between 3D rigid data (point clouds, meshes, or depth maps) is a fundamental problem in 3D computer vision.
no code implementations • 7 Jul 2019 • Yanqi Zhou, Peng Wang, Sercan Arik, Haonan Yu, Syed Zawad, Feng Yan, Greg Diamos
In this paper, we propose Efficient Progressive Neural Architecture Search (EPNAS), a neural architecture search (NAS) that efficiently handles large search space through a novel progressive search policy with performance prediction based on REINFORCE~\cite{Williams. 1992. PG}.
no code implementations • 29 Jul 2019 • Damien Teney, Peng Wang, Jiewei Cao, Lingqiao Liu, Chunhua Shen, Anton Van Den Hengel
One of the primary challenges faced by deep learning is the degree to which current methods exploit superficial statistics and dataset bias, rather than learning to generalise over the specific representations they have experienced.
no code implementations • 2 Sep 2019 • Linfeng Li, Peng Wang, Yao Wang, Jinpeng Jiang, Buzhou Tang, Jun Yan, Sheng-Hui Wang, Yu-Ting Liu
This paper proposes an algorithm named as PrTransH to learn embedding vectors from real world EMR data based medical knowledge.
no code implementations • 6 Sep 2019 • Xinyue Zheng, Peng Wang, Qigang Wang, Zhongchao shi, Feiyu Xu
NAS automatically generates and evaluates meta-learner's architecture for few-shot learning problems, while the meta-learner uses meta-learning algorithm to optimize its parameters based on the distribution of learning tasks.
no code implementations • 25 Oct 2019 • Shizhou Zhang, Yifei Yang, Peng Wang, Guoqiang Liang, Xiuwei Zhang, Yanning Zhang
The problem of cross-modality person re-identification has been receiving increasing attention recently, due to its practical significance.
Cross-Modality Person Re-identification Person Re-Identification
no code implementations • 6 Nov 2019 • Shuhan Yao, Jiuxiang Gu, Peng Wang, Tianyang Zhao, Huajun Zhang, Xiaochuan Liu
Mobile energy storage systems (MESSs) provide mobility and flexibility to enhance distribution system resilience.
no code implementations • 13 Nov 2019 • Xinjing Cheng, Peng Wang, Chenye Guan, Ruigang Yang
In this paper, we propose CSPN++, which further improves its effectiveness and efficiency by learning adaptive convolutional kernel sizes and the number of iterations for the propagation, thus the context and computational resources needed at each pixel could be dynamically assigned upon requests.
no code implementations • 10 Dec 2019 • Jun-Jie Zhang, Lingqiao Liu, Peng Wang, Chunhua Shen
Such imbalanced distribution causes a great challenge for learning a deep neural network, which can be boiled down into a dilemma: on the one hand, we prefer to increase the exposure of tail class samples to avoid the excessive dominance of head classes in the classifier training.
1 code implementation • 30 Jan 2020 • Alex D. Stivala, H. Colin Gallagher, David A. Rolls, Peng Wang, Garry L. Robins
Social science research increasingly benefits from statistical methods for understanding the structured nature of social life, including for social network data.
Social and Information Networks Methodology
no code implementations • 17 Feb 2020 • Wanyi Li, Fuyu Li, Yongkang Luo, Peng Wang, Jia Sun
Deep learning (DL) based object detection has achieved great progress.
no code implementations • CVPR 2020 • Zhenfang Chen, Peng Wang, Lin Ma, Kwan-Yee K. Wong, Qi Wu
To bridge the gap, we propose a new dataset for visual reasoning in context of referring expression comprehension with two main features.
1 code implementation • 9 Mar 2020 • Xiang Li, Peng Wang
Firstly, both communication parties establish a word vector table by training a deep learning model according to specified hyperparameters.
no code implementations • 2 Mar 2020 • Yitong Li, Dianqi Li, Sushant Prakash, Peng Wang
To improve the interpretability in the dual encoder models, we design a novel regularization loss to minimize the mutual information between unimportant words and desired labels, in addition to the original attention method, so that important words are emphasized while unimportant words are de-emphasized.
no code implementations • 26 Apr 2020 • Xinyue Zheng, Peng Wang, Qigang Wang, Zhongchao shi
Prior work in standardized science exams requires support from large text corpus, such as targeted science corpus fromWikipedia or SimpleWikipedia.
no code implementations • 6 Jun 2020 • Linjiang Zhang, Peng Wang, Hui Li, Zhen Li, Chunhua Shen, Yanning Zhang
On the other hand, the 2D attentional based license plate recognizer with an Xception-based CNN encoder is capable of recognizing license plates with different patterns under various scenarios accurately and robustly.
1 code implementation • 29 Jun 2020 • Peng Wang, Zirui Zhou, Anthony Man-Cho So
Community detection in graphs that are generated according to stochastic block models (SBMs) has received much attention lately.
no code implementations • 3 Jul 2020 • Xinjing Cheng, Peng Wang, Yanqi Zhou, Chenye Guan, Ruigang Yang
Omnidirectional 360{\deg} camera proliferates rapidly for autonomous robots since it significantly enhances the perception ability by widening the field of view(FoV).
no code implementations • ECCV 2020 • Yan Liu, Lingqiao Liu, Peng Wang, Pingping Zhang, Yinjie Lei
Most existing crowd counting systems rely on the availability of the object location annotation which can be expensive to obtain.
no code implementations • ICML 2020 • Peng Wang, Zirui Zhou, Anthony Man-Cho So
In this paper, we focus on the problem of exactly recovering the communities in a binary symmetric SBM, where a graph of $n$ vertices is partitioned into two equal-sized communities and the vertices are connected with probability $p = \alpha\log(n)/n$ within communities and $q = \beta\log(n)/n$ across communities for some $\alpha>\beta>0$.
no code implementations • 24 Sep 2020 • Xinyue Zheng, Peng Wang, Qigang Wang, Zhongchao shi
However, existing methods rely heavily on a black-box controller to search architectures, which suffers from the serious problem of lacking interpretability.
no code implementations • 13 Oct 2020 • Congqi Cao, Yajuan Li, Qinyi Lv, Peng Wang, Yanning Zhang
Few-shot learning aims to recognize instances from novel classes with few labeled samples, which has great value in research and application.
no code implementations • 17 Sep 2020 • Peng Wang, Yuanlin Zheng, Xianfeng Chen, Changming Huang, Yaroslav V. Kartashov, Lluis Torner, Vladimir V. Konotop, Fangwei Ye
Moire lattices consist of two identical periodic structures overlaid with a relative rotation angle.
Optics
no code implementations • 26 Oct 2020 • Haibo Su, Peng Wang, Lingqiao Liu, Hui Li, Zhen Li, Yanning Zhang
Fashion products typically feature in compositions of a variety of styles at different clothing parts.
no code implementations • 6 Dec 2020 • Peng Wang, Gang Xin, Yuwei Jiao
The mathematical relationship between the objective function and the wave function is established, and the quantum interpretation of the optimization problem is realized.
no code implementations • 13 Dec 2020 • Bolin Lai, YuHsuan Wu, Xiaoyu Bai, Xiao-Yun Zhou, Peng Wang, Jinzheng Cai, Yuankai Huo, Lingyun Huang, Yong Xia, Jing Xiao, Le Lu, Heping Hu, Adam Harrison
Using radiological scans to identify liver tumors is crucial for proper patient treatment.
no code implementations • 24 Dec 2020 • Peng Wang, Houwen Wu, Haitang Yang, Shuxuan Ying
It was proved more than three decades ago, that the first order $\alpha'$ correction of string effective theory could be written as the Gauss-Bonnet term, which is the quadratic term of Lovelock gravity.
High Energy Physics - Theory General Relativity and Quantum Cosmology High Energy Physics - Phenomenology
no code implementations • SEMEVAL 2020 • Qi Wu, Peng Wang, Chenghao Huang
Natural language processing (NLP) has been applied to various fields including text classification and sentiment analysis.
no code implementations • 5 Feb 2021 • Ming Ouyang, Xuesong Shi, Yujie Wang, Yuxin Tian, Yingzhe Shen, Dawei Wang, Peng Wang, Zhiqiang Cao
We present a collaborative visual simultaneous localization and mapping (SLAM) framework for service robots.
no code implementations • 1 Mar 2021 • Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang
In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.
no code implementations • 9 Mar 2021 • Bingliang Jiao, Xin Tan, Jinghao Zhou, Lu Yang, Yunlong Wang, Peng Wang
The proposed model is composed of three main branches where a self-guided dynamic branch is constructed to strengthen instance-specific features, focusing on every single image.
no code implementations • 9 Mar 2021 • Lu Yang, Hongbang Liu, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang, Yanning Zhang
Learning cross-view consistent feature representation is the key for accurate vehicle Re-identification (ReID), since the visual appearance of vehicles changes significantly under different viewpoints.
no code implementations • 18 Mar 2021 • Jinghao Zhou, Bo Li, Peng Wang, Peixia Li, Weihao Gan, Wei Wu, Junjie Yan, Wanli Ouyang
Visual Object Tracking (VOT) can be seen as an extended task of Few-Shot Learning (FSL).
no code implementations • 18 Mar 2021 • Jinghao Zhou, Bo Li, Lei Qiao, Peng Wang, Weihao Gan, Wei Wu, Junjie Yan, Wanli Ouyang
Visual Object Tracking (VOT) has synchronous needs for both robustness and accuracy.
no code implementations • 24 Mar 2021 • Bolin Lai, YuHsuan Wu, Xiao-Yun Zhou, Peng Wang, Le Lu, Lingyun Huang, Mei Han, Jing Xiao, Heping Hu, Adam P. Harrison
Lesion detection serves a critical role in early diagnosis and has been well explored in recent years due to methodological advancesand increased data availability.
no code implementations • CVPR 2021 • Peng Wang, Kai Han, Xiu-Shen Wei, Lei Zhang, Lei Wang
Learning discriminative image representations plays a vital role in long-tailed image classification because it can ease the classifier learning in imbalanced cases.
Ranked #10 on Long-tail Learning on CIFAR-10-LT (ρ=10)
no code implementations • 29 Mar 2021 • Lei Tian, Guoqiang Liang, Peng Wang, Chunhua Shen
Because of the invisible human keypoints in images caused by illumination, occlusion and overlap, it is likely to produce unreasonable human pose prediction for most of the current human pose estimation methods.
no code implementations • 8 Apr 2021 • Wei W. Xing, Akeel A. Shah, Peng Wang, Shandian Zhe Qian Fu, Robert. M. Kirby
The resulting model is equipped with a closed-form solution for the predictive posterior, making it applicable to advanced, high-dimensional tasks that require uncertainty estimation.
no code implementations • 15 Apr 2021 • Chao Cai, Ruinan Jin, Peng Wang, Liyuan Ye, Hongbo Jiang, Jun Luo
Recently, \textit{passive behavioral biometrics} (e. g., gesture or footstep) have become promising complements to conventional user identification methods (e. g., face or fingerprint) under special situations, yet existing sensing technologies require lengthy measurement traces and cannot identify multiple users at the same time.
no code implementations • 30 Apr 2021 • Weidong Lin, Yuyan Deng, Yang Gao, Ning Wang, Jinghao Zhou, Lingqiao Liu, Lei Zhang, Peng Wang
Given a query patch from a novel class, one-shot object detection aims to detect all instances of that class in a target image through the semantic similarity comparison.