no code implementations • NAACL (SocialNLP) 2022 • Shuo Yang
Specifically, we train a multilayer perceptron (MLP) as a style classifier to find out and mask style-characteristic words in the source inputs.
no code implementations • 11 Dec 2024 • Zirui Shang, Yubo Zhu, Hongxi Li, Shuo Yang, Xinxiao wu
Specifically, we propose a novel diffusion summarization method based on the Denoising Diffusion Probabilistic Model (DDPM), which learns the probability distribution of training data through noise prediction, and generates summaries by iterative denoising.
no code implementations • 10 Dec 2024 • Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
Compared with unsupervised SoTA models, RAZOR improves by 3. 5% on the FEVER and 6. 5% on MNLI and SNLI datasets according to the F1 score.
no code implementations • 25 Nov 2024 • Yilong Zhao, Shuo Yang, Kan Zhu, Lianmin Zheng, Baris Kasikci, Yang Zhou, Jiarong Xing, Ion Stoica
Offline batch inference, which leverages the flexibility of request batching to achieve higher throughput and lower costs, is becoming more popular for latency-insensitive applications.
no code implementations • 5 Nov 2024 • Shuo Yang, Siwen Luo, Soyeon Caren Han
Existing Multimodal Large Language Models (MLLMs) and Visual Language Pretrained Models (VLPMs) have shown remarkable performances in the general Visual Question Answering (VQA).
no code implementations • 29 Oct 2024 • Zhong Ji, Shuo Yang, Jingren Liu, Yanwei Pang, Jungong Han
Generalized Category Discovery (GCD) aims to classify both base and novel images using labeled base data.
no code implementations • 28 Oct 2024 • Kunyun Wang, Jieru Zhao, Shuo Yang, Wenchao Ding, Minyi Guo
To address these issues, we propose a memory-efficient scheduling method to eliminate memory overhead and an online adjustment mechanism to minimize accuracy degradation.
no code implementations • 16 Oct 2024 • Handi Chen, Weipeng Deng, Shuo Yang, Jinfeng Xu, Zhihan Jiang, Edith C. H. Ngai, Jiangchuan Liu, Xue Liu
The integration of Large Language Models (LLMs) empowers EI to evolve into the next stage: Edge General Intelligence (EGI), enabling more adaptive and versatile applications that require advanced understanding and reasoning capabilities.
no code implementations • 14 Oct 2024 • Shuo Yang, Kun-Peng Ning, Yu-Yang Liu, Jia-Yu Yao, Yong-Hong Tian, Yi-Bing Song, Li Yuan
Large Language Models (LLMs) often suffer from catastrophic forgetting when learning multiple tasks sequentially, making continual learning (CL) essential for their dynamic deployment.
no code implementations • 19 Sep 2024 • Yongqi Wang, Shuo Yang, Xinxiao wu, Jiebo Luo
To address this challenge, we propose to unify object trajectory detection and relationship classification into an end-to-end open-vocabulary framework.
1 code implementation • 4 Sep 2024 • Jinfeng Xu, Zheyu Chen, Jinze Li, Shuo Yang, Hewei Wang, Edith C. -H. Ngai
Extensive experiments on two real-world datasets validate that our AlignGroup outperforms the state-of-the-art on both the group recommendation task and the user recommendation task, as well as outperforms the efficiency of most baselines.
no code implementations • 26 Aug 2024 • Nikhil Khani, Shuo Yang, Aniruddh Nath, Yang Liu, Pendo Abbo, Li Wei, Shawn Andrews, Maciej Kula, Jarrod Kahn, Zhe Zhao, Lichan Hong, Ed Chi
Knowledge Distillation (KD) is a powerful approach for compressing a large model into a smaller, more efficient model, particularly beneficial for latency-sensitive applications like recommender systems.
no code implementations • 23 Aug 2024 • Shuo Yang, Shizhen Li, Yanjun Huang, Hong Chen
The results show that the proposed algorithm can generate safe and reasonable actions in a variety of complex scenarios and guarantee safety without losing the evolutionary potential of learning-based autonomous driving systems.
no code implementations • 22 Aug 2024 • Shuo Yang, LiWen Wang, Yanjun Huang, Hong Chen
Autonomous vehicles with a self-evolving ability are expected to cope with unknown scenarios in the real-world environment.
1 code implementation • 11 Aug 2024 • Shuo Yang, Ying Sheng, Joseph E. Gonzalez, Ion Stoica, Lianmin Zheng
Our key insight is that the pattern of channel sparsity is relatively static, allowing us to use offline calibration to make it efficient at runtime, thereby enabling accurate and efficient identification of important tokens.
no code implementations • 15 Jul 2024 • Shuo Yang, Zhengshuo Li, Ye Tian
This model comprehensively considers the flexible devices in the FDN and the impact of uncertainty of photovoltaic power generation and load.
no code implementations • 17 Jun 2024 • Shuo Yang, Chenchen Yuan, Yao Rong, Felix Steinbauer, Gjergji Kasneci
A multitude of industries depend on accurate and reasonable tabular data augmentation for their business processes.
1 code implementation • 3 Jun 2024 • Jinfeng Xu, Zheyu Chen, Jinze Li, Shuo Yang, Wei Wang, Xiping Hu, Edith C. -H. Ngai
We revisit these two components and discover that a part of feature transformation and nonlinear operation during message passing in GCN can improve the representation of GCF, but increase the difficulty of training.
no code implementations • 29 May 2024 • Xuan Son Nguyen, Shuo Yang, Aymeric Histace
Recently, some works have shown that many concepts in the theory of gyrogroups and gyrovector spaces can also be generalized to matrix manifolds such as Symmetric Positive Definite (SPD) and Grassmann manifolds.
1 code implementation • 30 Mar 2024 • Wentao Xu, Qianqian Xie, Shuo Yang, Jiangxia Cao, Shuchao Pang
However, they still neglect the following two points: (1) The content semantic is a universal world knowledge; how do we extract the multi-aspect semantic information to empower different domains?
no code implementations • 25 Mar 2024 • Tom Kuipers, Renukanandan Tumu, Shuo Yang, Milad Kazemi, Rahul Mangharam, Nicola Paoletti
A key contribution of MA-COPP is to avoid enumeration or exhaustive search of the output space of agent trajectories, which is instead required by existing COPP methods to construct the prediction region.
no code implementations • 2 Mar 2024 • Shuo Yang, Zirui Shang, Yongqi Wang, Derong Deng, Hongwei Chen, Qiyuan Cheng, Xinxiao wu
This paper proposes a novel framework for multi-label image recognition without any training data, called data-free framework, which uses knowledge of pre-trained Large Language Model (LLM) to learn prompts to adapt pretrained Vision-Language Model (VLM) like CLIP to multilabel classification.
1 code implementation • 29 Feb 2024 • Jinfeng Xu, Zheyu Chen, Shuo Yang, Jinze Li, Hewei Wang, Edith C. -H. Ngai
It utilizes multimodal information to alleviate the data sparsity problem in recommendation systems, thus improving recommendation accuracy.
no code implementations • 28 Feb 2024 • Shuo Yang, Gjergji Kasneci
This research significantly reduces training costs of proximal policy-guided models and demonstrates the potential for self-correction of language models.
1 code implementation • 2 Feb 2024 • Kun-Peng Ning, Shuo Yang, Yu-Yang Liu, Jia-Yu Yao, Zhen-Hui Liu, Yu Wang, Ming Pang, Li Yuan
Existing large language models (LLMs) evaluation methods typically focus on testing the performance on some closed-environment and domain-specific benchmarks with human annotations.
1 code implementation • 30 Jan 2024 • Xinyu Lin, Wenjie Wang, Yongqi Li, Shuo Yang, Fuli Feng, Yinwei Wei, Tat-Seng Chua
To pursue the two objectives, we propose a novel data pruning method based on two scores, i. e., influence score and effort score, to efficiently identify the influential samples.
1 code implementation • 26 Jan 2024 • Shuo Yang, Yu Chen, Xiang Yin, George J. Pappas, Rahul Mangharam
Our approach is computationally efficient, minimally invasive to any reference controller, and applicable to large-scale systems.
no code implementations • 8 Dec 2023 • Yakun Wang, Binbin Hu, Shuo Yang, Meiqi Zhu, Zhiqiang Zhang, Qiyang Zhang, Jun Zhou, Guo Ye, Huimei He
In particular, we elaborately devise a Meta-learning Supported Teacher-student GNN (MST-GNN) that is not only built upon teacher-student architecture for alleviating the migration between "easy" and "hard" samples but also equipped with a meta learning based sample re-weighting module for helping the student GNN distinguish "hard" samples in a fine-grained manner.
1 code implementation • 8 Nov 2023 • Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, Joseph E. Gonzalez, Ion Stoica
Many have raised concerns about the trustworthiness of public benchmarks due to potential contamination in pre-training or fine-tuning datasets.
2 code implementations • 6 Nov 2023 • Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica
To capitalize on these opportunities, we present S-LoRA, a system designed for the scalable serving of many LoRA adapters.
1 code implementation • 19 Sep 2023 • Luigi Berducci, Shuo Yang, Rahul Mangharam, Radu Grosu
Ensuring safety in dynamic multi-agent systems is challenging due to limited information about the other agents.
1 code implementation • 31 Aug 2023 • Yuyan Zhou, Dong Liang, Songcan Chen, Sheng-Jun Huang, Shuo Yang, Chongyi Li
In this paper, we propose a solution to improve the performance of lens flare removal by revisiting the ISP and remodeling the principle of automatic exposure in the synthesis pipeline and design a more reliable light sources recovery strategy.
no code implementations • 11 Jun 2023 • Jiangwei Wang, Shuo Yang, Ziyan An, Songyang Han, Zhili Zhang, Rahul Mangharam, Meiyi Ma, Fei Miao
The STL requirements are designed to include both task specifications according to the objective of each agent and safety specifications, and the robustness values of the STL specifications are leveraged to generate rewards.
Deep Reinforcement Learning Multi-agent Reinforcement Learning +1
1 code implementation • 8 Jun 2023 • Muyang He, Shuo Yang, Tiejun Huang, Bo Zhao
The state of the art of many learning tasks, e. g., image classification, is advanced by collecting larger datasets and then training larger models on them.
no code implementations • 8 May 2023 • Xuan Son Nguyen, Shuo Yang
Recently, by applying the theory of gyrogroups and gyrovector spaces that is a powerful framework for studying hyperbolic geometry, some works have attempted to build principled generalizations of Euclidean neural networks on matrix manifolds.
1 code implementation • 3 Apr 2023 • Qinglin Liu, Xiaoqian Lv, Quanling Meng, Zonglin Li, Xiangyuan Lan, Shuo Yang, Shengping Zhang, Liqiang Nie
Furthermore, AEMatter leverages a large image training strategy to assist the network in learning context aggregation from data.
Ranked #1 on Image Matting on Composition-1K
no code implementations • 1 Apr 2023 • Shuo Yang, George J. Pappas, Rahul Mangharam, Lars Lindemann
However, these perception maps are not perfect and result in state estimation errors that can lead to unsafe system behavior.
1 code implementation • CVPR 2023 • Shuo Yang, Zhaopan Xu, Kai Wang, Yang You, Hongxun Yao, Tongliang Liu, Min Xu
As one of the most fundamental techniques in multimodal learning, cross-modal matching aims to project various sensory modalities into a shared feature space.
Cross-modal retrieval with noisy correspondence Image-text matching +1
1 code implementation • 1 Mar 2023 • Xiatao Sun, Shuo Yang, Mingyan Zhou, Kunpeng Liu, Rahul Mangharam
In this paper, we propose MEGA-DAgger, a new DAgger variant that is suitable for interactive learning with multiple imperfect experts.
no code implementations • 28 Feb 2023 • Zhengzhuo Xu, Shuo Yang, Xingjun Wang, Chun Yuan
Hence, we propose to adopt unsupervised learning to utilize long-tailed data.
1 code implementation • 1 Feb 2023 • Yinghui Xing, Shuo Yang, Song Wang, Shizhou Zhang, Guoqiang Liang, Xiuwei Zhang, Yanning Zhang
Multispectral pedestrian detection is an important task for many around-the-clock applications, since the visible and thermal modalities can provide complementary information especially under low light conditions.
1 code implementation • ICCV 2023 • Gengshan Yang, Shuo Yang, John Z. Zhang, Zachary Manchester, Deva Ramanan
Given monocular videos, we build 3D models of articulated objects and environments whose 3D configurations satisfy dynamics and contact constraints.
1 code implementation • ICCV 2023 • Yuyan Zhou, Dong Liang, Songcan Chen, Sheng-Jun Huang, Shuo Yang, Chongyi Li
In this paper, we propose a solution to improve the performance of lens flare removal by revisiting the ISP and remodeling the principle of automatic exposure in the synthesis pipeline and design a more reliable light sources recovery strategy.
no code implementations • ICCV 2023 • Shan He, Haonan He, Shuo Yang, Xiaoyan Wu, Pengcheng Xia, Bing Yin, Cong Liu, LiRong Dai, Chang Xu
Besides, we also verify that the proposed framework is able to explicitly control the emotion of the animated talking face.
no code implementations • 11 Dec 2022 • Shuo Yang, Yang Jiao, Shaoyu Dou, Mana Zheng, Chen Zhu
The bilevel optimization is used to automatically update the hyperparameter, and the gradient of the hyperparameter is the approximate gradient based on the best response function.
1 code implementation • CVPR 2023 • Zhengzhuo Xu, Ruikang Liu, Shuo Yang, Zenghao Chai, Chun Yuan
In this paper, we systematically investigate the ViTs' performance in LTR and propose LiVT to train ViTs from scratch only with LT data.
Ranked #7 on Long-tail Learning on CIFAR-10-LT (ρ=10)
no code implementations • 23 Nov 2022 • Yu Chen, Shuo Yang, Rahul Mangharam, Xiang Yin
This problem is particularly challenging since future information is involved in the synthesis process.
no code implementations • 27 Sep 2022 • Rahul Duggal, Hao Zhou, Shuo Yang, Jun Fang, Yuanjun Xiong, Wei Xia
With the shift towards on-device deep learning, ensuring a consistent behavior of an AI service across diverse compute platforms becomes tremendously important.
no code implementations • 20 Sep 2022 • Shuo Yang, Shaoru Chen, Victor M. Preciado, Rahul Mangharam
Learning-based controllers, such as neural network (NN) controllers, can show high empirical performance but lack formal safety guarantees.
no code implementations • 19 Sep 2022 • Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan
Such features naturally arise in merchandised recommendation systems; for instance, "user clicked this item" as a feature is predictive of "user purchased this item" in the offline data, but is clearly not available during online serving.
no code implementations • 27 Jul 2022 • Borui Ye, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Youqiang He, Kai Huang, Jun Zhou, Yanming Fang
E-commerce has gone a long way in empowering merchants through the internet.
no code implementations • 19 May 2022 • Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, Ping Li
To answer these, we propose dataset pruning, an optimization-based sample selection method that can (1) examine the influence of removing a particular set of training samples on model's generalization ability with theoretical guarantee, and (2) construct the smallest subset of training data that yields strictly constrained generalization gap.
1 code implementation • 12 May 2022 • Shuo Yang, Xinxiao wu
Language-driven action localization in videos is a challenging task that involves not only visual-linguistic matching but also action boundary prediction.
1 code implementation • 12 May 2022 • Yue Zhao, Yantao Shen, Yuanjun Xiong, Shuo Yang, Wei Xia, Zhuowen Tu, Bernt Schiele, Stefano Soatto
Based on the observation, we present a method, called Ensemble Logit Difference Inhibition (ELODI), to train a classification system that achieves paragon performance in both error rate and NFR, at the inference cost of a single model.
1 code implementation • 30 Apr 2022 • Kai Wang, Xiangyu Peng, Shuo Yang, Jianfei Yang, Zheng Zhu, Xinchao Wang, Yang You
This paradigm, however, is prone to significant degeneration under heavy label noise, as the number of clean samples is too small for conventional methods to behave well.
2 code implementations • CVPR 2022 • Kai Wang, Bo Zhao, Xiangyu Peng, Zheng Zhu, Shuo Yang, Shuo Wang, Guan Huang, Hakan Bilen, Xinchao Wang, Yang You
Dataset condensation aims at reducing the network training effort through condensing a cumbersome training set into a compact synthetic one.
1 code implementation • 1 Mar 2022 • Qian Zhao, Shuo Yang, Binbin Hu, Zhiqiang Zhang, Yakun Wang, Yusong Chen, Jun Zhou, Chuan Shi
Temporal link prediction, as one of the most crucial work in temporal graphs, has attracted lots of attention from the research area.
no code implementations • 24 Feb 2022 • Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S. Dhillon, Sujay Sanghavi, Qi Lei
Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data.
1 code implementation • 13 Dec 2021 • Dong Liang, Ling Li, Mingqiang Wei, Shuo Yang, Liyan Zhang, Wenhan Yang, Yun Du, Huiyu Zhou
Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images.
1 code implementation • 2 Dec 2021 • Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Qihang Yu, Alan Yuille
To help address this problem, we propose PartImageNet, a large, high-quality dataset with part segmentation annotations.
no code implementations • NeurIPS 2021 • Zhao Song, Shuo Yang, Ruizhe Zhang
The classical training method requires paying $\Omega(mnd)$ cost for both forward computation and backward computation, where $m$ is the width of the neural network, and we are given $n$ training points in $d$-dimensional space.
no code implementations • 8 Oct 2021 • Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou
Our approach exploits the special structure of BERT that contains a stack of repeated modules (i. e., transformer encoders).
no code implementations • ICLR 2022 • Shuo Yang, Peize Sun, Yi Jiang, Xiaobo Xia, Ruiheng Zhang, Zehuan Yuan, Changhu Wang, Ping Luo, Min Xu
A more realistic object detection paradigm, Open-World Object Detection, has arisen increasing research interests in the community recently.
no code implementations • 29 Sep 2021 • Shuo Yang, Yijun Dong, Rachel Ward, Inderjit S Dhillon, Sujay Sanghavi, Qi Lei
Data augmentation is popular in the training of large neural networks; currently, however, there is no clear theoretical comparison between different algorithmic choices on how to use augmented data.
no code implementations • 6 Jul 2021 • Wei Li, Yuanjun Xiong, Shuo Yang, Mingze Xu, Yongxin Wang, Wei Xia
We design a new instance-to-track matching objective to learn appearance embedding that compares a candidate detection to the embedding of the tracks persisted in the tracker.
no code implementations • 27 May 2021 • Shuo Yang, Erkun Yang, Bo Han, Yang Liu, Min Xu, Gang Niu, Tongliang Liu
Motivated by that classifiers mostly output Bayes optimal labels for prediction, in this paper, we study to directly model the transition from Bayes optimal labels to noisy labels (i. e., Bayes-label transition matrix (BLTM)) and learn a classifier to predict Bayes optimal labels.
no code implementations • CVPR 2021 • Rahul Duggal, Hao Zhou, Shuo Yang, Yuanjun Xiong, Wei Xia, Zhuowen Tu, Stefano Soatto
Existing systems use the same embedding model to compute representations (embeddings) for the query and gallery images.
no code implementations • 13 Mar 2021 • Jiahao Xia, Haimin Zhang, Shiping Wen, Shuo Yang, Min Xu
Moreover, we generate a cheap heatmap based on the face alignment result and fuse it with features to improve the performance of the other two tasks.
Ranked #28 on Face Alignment on WFLW
no code implementations • 3 Mar 2021 • Shuo Yang, Tongzheng Ren, Inderjit S. Dhillon, Sujay Sanghavi
Specifically, we focus on a challenging setting where 1) the reward distribution of an arm depends on the set $s$ it is part of, and crucially 2) there is \textit{no total order} for the arms in $\mathcal{A}$.
no code implementations • 3 Mar 2021 • Shuo Yang, Tongzheng Ren, Sanjay Shakkottai, Eric Price, Inderjit S. Dhillon, Sujay Sanghavi
For sufficiently large $K$, our algorithms have sublinear per-step complexity and $\tilde O(\sqrt{T})$ regret.
1 code implementation • 25 Feb 2021 • Yuanhan Zhang, Zhenfei Yin, Jing Shao, Ziwei Liu, Shuo Yang, Yuanjun Xiong, Wei Xia, Yan Xu, Man Luo, Jian Liu, Jianshu Li, Zhijun Chen, Mingyu Guo, Hui Li, Junfu Liu, Pengfei Gao, Tianqi Hong, Hao Han, Shijie Liu, Xinhua Chen, Di Qiu, Cheng Zhen, Dashuang Liang, Yufeng Jin, Zhanlong Hao
It is the largest face anti-spoofing dataset in terms of the numbers of the data and the subjects.
2 code implementations • 18 Feb 2021 • Liming Jiang, Zhengkui Guo, Wayne Wu, Zhaoyang Liu, Ziwei Liu, Chen Change Loy, Shuo Yang, Yuanjun Xiong, Wei Xia, Baoying Chen, Peiyu Zhuang, Sili Li, Shen Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Liujuan Cao, Rongrong Ji, Changlei Lu, Ganchao Tan
This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection.
no code implementations • IWSLT (ACL) 2022 • Di wu, Liang Ding, Shuo Yang, Mingyang Li
Recently, the performance of the neural word alignment models has exceeded that of statistical models.
6 code implementations • ICLR 2021 • Shuo Yang, Lu Liu, Min Xu
In this paper, we calibrate the distribution of these few-sample classes by transferring statistics from the classes with sufficient examples, then an adequate number of examples can be sampled from the calibrated distribution to expand the inputs to the classifier.
no code implementations • 1 Jan 2021 • Di wu, Liang Ding, Shuo Yang, DaCheng Tao
Recently, the performance of the neural word alignment models has exceeded that of statistical models.
no code implementations • 1 Jan 2021 • Shuo Yang, Le Hou, Xiaodan Song, Qiang Liu, Denny Zhou
It has been widely observed that increasing deep learning model sizes often leads to significant performance improvements on a variety of natural language processing and computer vision tasks.
no code implementations • 31 Dec 2020 • Jian-Hao Zhang, Shuo Yang, Yang Qi, Zheng-Cheng Gu
The construction and classification of crystalline symmetry protected topological (SPT) phases in interacting bosonic and fermionic systems have been intensively studied in the past few years.
Strongly Correlated Electrons Mesoscale and Nanoscale Physics Mathematical Physics Mathematical Physics
no code implementations • 24 Nov 2020 • Thomas Matheson, Carl Stubens, Nicholas Wolf, Chien-Hsiu Lee, Gautham Narayan, Abhijit Saha, Adam Scott, Monika Soraisam, Adam S. Bolton, Benjamin Hauger, David R. Silva, John Kececioglu, Carlos Scheidegger, Richard Snodgrass, Patrick D. Aleo, Eric Evans-Jacquez, Navdeep Singh, Zhe Wang, Shuo Yang, Zhenge Zhao
We describe the Arizona-NOIRLab Temporal Analysis and Response to Events System (ANTARES), a software instrument designed to process large-scale streams of astronomical time-domain alerts.
Instrumentation and Methods for Astrophysics
no code implementations • CVPR 2021 • Sijie Yan, Yuanjun Xiong, Kaustav Kundu, Shuo Yang, Siqi Deng, Meng Wang, Wei Xia, Stefano Soatto
Reducing inconsistencies in the behavior of different versions of an AI system can be as important in practice as reducing its overall error.
1 code implementation • 30 Oct 2020 • Wei Li, Yuanjun Xiong, Shuo Yang, Siqi Deng, Wei Xia
We combine this scheme with SSD detectors by proposing a novel tracking anchor assignment module.
2 code implementations • CVPR 2020 • Guan'an Wang, Shuo Yang, Huanyu Liu, Zhicheng Wang, Yang Yang, Shuliang Wang, Gang Yu, Erjin Zhou, Jian Sun
When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.
no code implementations • CVPR 2021 • Shuo Yang, Min Xu, Haozhe Xie, Stuart Perry, Jiahao Xia
Inspired by this, we propose a novel method, named Mem3D, that explicitly constructs shape priors to supplement the missing information in the image.
no code implementations • 8 Mar 2020 • Shuo Yang, Wei Yu, Ying Zheng, Hongxun Yao, Tao Mei
To solve this new problem, we propose a hierarchical adaptive semantic-visual tree (ASVT) to depict the architecture of merchandise categories, which evaluates semantic similarities between different semantic levels and visual similarities within the same semantic class simultaneously.
no code implementations • NeurIPS 2019 • Shuo Yang, Yanyao Shen, Sujay Sanghavi
In this paper, we provide a new algorithm - Interaction Hard Thresholding (IntHT) which is the first one to provably accurately solve this problem in sub-quadratic time and space.
1 code implementation • ICCV 2019 • Keqiang Sun, Wayne Wu, Tinghao Liu, Shuo Yang, Quan Wang, Qiang Zhou, Zuochang Ye, Chen Qian
A structure predictor is proposed to predict the missing face structural information temporally, which serves as a geometry prior.
no code implementations • 10 Sep 2019 • Shuo Yang, Wei zhang, Weizhi Lu, Hesheng Wang, Yibin Li
However, the general video captioning methods focus more on the understanding of the full frame, lacking of consideration on the specific object of interests in robotic manipulations.
no code implementations • 19 Feb 2019 • Chen Change Loy, Dahua Lin, Wanli Ouyang, Yuanjun Xiong, Shuo Yang, Qingqiu Huang, Dongzhan Zhou, Wei Xia, Quanquan Li, Ping Luo, Junjie Yan, Jian-Feng Wang, Zuoxin Li, Ye Yuan, Boxun Li, Shuai Shao, Gang Yu, Fangyun Wei, Xiang Ming, Dong Chen, Shifeng Zhang, Cheng Chi, Zhen Lei, Stan Z. Li, Hongkai Zhang, Bingpeng Ma, Hong Chang, Shiguang Shan, Xilin Chen, Wu Liu, Boyan Zhou, Huaxiong Li, Peng Cheng, Tao Mei, Artem Kukharenko, Artem Vasenin, Nikolay Sergievskiy, Hua Yang, Liangqi Li, Qiling Xu, Yuan Hong, Lin Chen, Mingjun Sun, Yirong Mao, Shiying Luo, Yongjun Li, Ruiping Wang, Qiaokang Xie, Ziyang Wu, Lei Lu, Yiheng Liu, Wengang Zhou
This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian.
2 code implementations • CVPR 2019 • Jiaqi Wang, Kai Chen, Shuo Yang, Chen Change Loy, Dahua Lin
State-of-the-art detectors mostly rely on a dense anchoring scheme, where anchors are sampled uniformly over the spatial domain with a predefined set of scales and aspect ratios.
Ranked #1 on Region Proposal on COCO test-dev
no code implementations • 2 Nov 2018 • Shuo Yang
It also demonstrates the outstanding performance of these proposed models as well as other state of the art machine learning models when applied to medical research problems and other real-world large-scale systems, reveals the great potential of statistical relational learning for exploring the structured health-related data to facilitate medical research.
no code implementations • ICLR 2018 • Kenny J. Young, Richard S. Sutton, Shuo Yang
We suggest one advantage of this particular type of memory is the ability to easily assign credit to a specific state when remembered information is found to be useful.
2 code implementations • CVPR 2018 • Wayne Wu, Chen Qian, Shuo Yang, Quan Wang, Yici Cai, Qiang Zhou
By utilising boundary information of 300-W dataset, our method achieves 3. 92% mean error with 0. 39% failure rate on COFW dataset, and 1. 25% mean error on AFLW-Full dataset.
Ranked #4 on Face Alignment on AFLW-19 (using extra training data)
1 code implementation • CVPR 2018 • Kai Chen, Jiaqi Wang, Shuo Yang, Xingcheng Zhang, Yuanjun Xiong, Chen Change Loy, Dahua Lin
High-performance object detection relies on expensive convolutional networks to compute features, often leading to significant challenges in applications, e. g. those that require detecting objects from video streams in real time.
no code implementations • CVPR 2017 2017 • Wenyan Wu, Shuo Yang
Face alignment is a critical topic in the computer vision community.
Ranked #35 on Face Alignment on WFLW
no code implementations • 9 Jun 2017 • Shuo Yang, Yuanjun Xiong, Chen Change Loy, Xiaoou Tang
Specifically, our method achieves 76. 4 average precision on the challenging WIDER FACE dataset and 96% recall rate on the FDDB dataset with 7 frames per second (fps) for 900 * 1300 input image.
19 code implementations • CVPR 2017 • Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, Xiaoou Tang
In this work, we propose "Residual Attention Network", a convolutional neural network using attention mechanism which can incorporate with state-of-art feed forward network architecture in an end-to-end training fashion.
Ranked #684 on Image Classification on ImageNet
no code implementations • 7 Apr 2017 • Xiaoming Deng, Shuo Yang, yinda zhang, Ping Tan, Liang Chang, Hongan Wang
We propose a novel 3D neural network architecture for 3D hand pose estimation from a single depth image.
no code implementations • 29 Jan 2017 • Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang
We propose a deep convolutional neural network (CNN) for face detection leveraging on facial attributes based supervision.
no code implementations • 8 Dec 2016 • Xiaoming Deng, Ye Yuan, Yinda Zhang, Ping Tan, Liang Chang, Shuo Yang, Hongan Wang
Hand detection is essential for many hand related tasks, e. g. parsing hand pose, understanding gesture, which are extremely useful for robotics and human-computer interaction.
no code implementations • 4 Jul 2016 • Shuo Yang, Mohammed Korayem, Khalifeh Aljadda, Trey Grainger, Sriraam Natarajan
In this paper, we proposed a way to adapt the state-of-the-art in SRL learning approaches to construct a real hybrid recommendation system.
1 code implementation • CVPR 2016 • Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang
Face detection is one of the most studied topics in the computer vision community.
Ranked #34 on Face Detection on WIDER Face (Medium)
1 code implementation • ICCV 2015 • Shuo Yang, Ping Luo, Chen Change Loy, Xiaoou Tang
In this paper, we propose a novel deep convolutional network (DCN) that achieves outstanding performance on FDDB, PASCAL Face, and AFW.
no code implementations • CVPR 2015 • Wanli Ouyang, Xiaogang Wang, Xingyu Zeng, Shi Qiu, Ping Luo, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Chen-Change Loy, Xiaoou Tang
In this paper, we propose deformable deep convolutional neural networks for generic object detection.
no code implementations • 11 Sep 2014 • Wanli Ouyang, Ping Luo, Xingyu Zeng, Shi Qiu, Yonglong Tian, Hongsheng Li, Shuo Yang, Zhe Wang, Yuanjun Xiong, Chen Qian, Zhenyao Zhu, Ruohui Wang, Chen-Change Loy, Xiaogang Wang, Xiaoou Tang
In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and penalty.