1 code implementation • ECCV 2020 • Zixuan Chen, Zhihui Xie, Junchi Yan Yinqiang Zheng, Xiaokang Yang
In this paper, we treat the graphs as graphs on a super-graph, and propose a novel breadth first search based method for expanding the neighborhood on the super-graph for a new coming graph, such that the matching with the new graph can be efficiently performed within the constructed neighborhood.
no code implementations • 6 Dec 2022 • Zanwei Zhou, RuiZhe Zhong, Chen Yang, Yan Wang, Xiaokang Yang, Wei Shen
In this study, we point out that the current tokenization strategy in MTSF Transformer architectures ignores the token uniformity inductive bias of Transformers.
no code implementations • 13 Oct 2022 • Shuai Jia, Bangjie Yin, Taiping Yao, Shouhong Ding, Chunhua Shen, Xiaokang Yang, Chao Ma
For face recognition attacks, existing methods typically generate the l_p-norm perturbations on pixels, however, resulting in low attack transferability and high vulnerability to denoising defense models.
no code implementations • 3 Oct 2022 • Weixia Zhang, Dingquan Li, Xiongkuo Min, Guangtao Zhai, Guodong Guo, Xiaokang Yang, Kede Ma
No-reference image quality assessment (NR-IQA) aims to quantify how humans perceive visual distortions of digital images without access to their undistorted references.
no code implementations • 6 Jul 2022 • Huiyu Duan, Guangtao Zhai, Xiongkuo Min, Yucheng Zhu, Yi Fang, Xiaokang Yang
The original and distorted omnidirectional images, subjective quality ratings, and the head and eye movement data together constitute the OIQA database.
no code implementations • 4 Jul 2022 • Wei Shen, Zelin Peng, Xuehui Wang, Huayu Wang, Jiazhong Cen, Dongsheng Jiang, Lingxi Xie, Xiaokang Yang, Qi Tian
The rapid development of deep learning has made a great progress in segmentation, one of the fundamental tasks of computer vision.
1 code implementation • 27 May 2022 • Minting Pan, Xiangming Zhu, Yunbo Wang, Xiaokang Yang
First, by optimizing the inverse dynamics, we encourage the world model to learn controllable and noncontrollable sources of spatiotemporal changes on isolated state transition branches.
no code implementations • 28 Apr 2022 • Shaofeng Zhang, Feng Zhu, Junchi Yan, Rui Zhao, Xiaokang Yang
Scalability is an important consideration for deep graph neural networks.
1 code implementation • CVPR 2022 • Geng Chen, Wendong Zhang, Han Lu, Siyu Gao, Yunbo Wang, Mingsheng Long, Xiaokang Yang
Can we develop predictive learning algorithms that can deal with more realistic, non-stationary physical environments?
1 code implementation • 11 Apr 2022 • Huiyu Duan, Xiongkuo Min, Yucheng Zhu, Guangtao Zhai, Xiaokang Yang, Patrick Le Callet
An objective metric termed CFIQA is also proposed to better evaluate the confusing image quality.
1 code implementation • IEEE Transactions on Knowledge and Data Engineering 2021 • Chao Chen, Dongsheng Li, Junchi Yan, Xiaokang Yang
Capturing the dynamics in user preference is crucial to better predict user future behaviors because user preferences often drift over time.
1 code implementation • 30 Mar 2022 • Chao Chen, Haoyu Geng, Nianzu Yang, Junchi Yan, Daiyue Xue, Jianping Yu, Xiaokang Yang
User interests are usually dynamic in the real world, which poses both theoretical and practical challenges for learning accurate preferences from rich behavior data.
no code implementations • CVPR 2022 • Shuai Jia, Chao Ma, Taiping Yao, Bangjie Yin, Shouhong Ding, Xiaokang Yang
In addition, the proposed frequency attack enhances the transferability across face forgery detectors as black-box attacks.
1 code implementation • 22 Mar 2022 • Xiaokang Yang, Gongmin Yan, Fan Liu, Bofan Guan, Sihai Li
Compared with the Monte-Carlo method and other method based on covariance matrix, the proposed method uses more complete error model, considers the interaction effect of error sources and can be easily realized with less computation.
no code implementations • 21 Mar 2022 • Xiaoxing Wang, Jiale Lin, Junchi Yan, Juanping Zhao, Xiaokang Yang
In contrast, this paper introduces an efficient framework, named EAutoDet, that can discover practical backbone and FPN architectures for object detection in 1. 4 GPU-days.
Ranked #23 on
Object Detection In Aerial Images
on DOTA
1 code implementation • 18 Mar 2022 • Xingyu Ren, Alexandros Lattas, Baris Gecer, Jiankang Deng, Chao Ma, Xiaokang Yang, Stefanos Zafeiriou
Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed.
no code implementations • 15 Mar 2022 • Liang Xu, Ziyang Song, Dongliang Wang, Jing Su, Zhicheng Fang, Chenjing Ding, Weihao Gan, Yichao Yan, Xin Jin, Xiaokang Yang, Wenjun Zeng, Wei Wu
We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions.
no code implementations • 15 Mar 2022 • Zanwei Zhou, Zi Wang, Shunyu Yao, Yichao Yan, Chen Yang, Guangtao Zhai, Junchi Yan, Xiaokang Yang
Conversation is an essential component of virtual avatar activities in the metaverse.
no code implementations • 3 Mar 2022 • Shanyan Guan, Huayu Deng, Yunbo Wang, Xiaokang Yang
Deep learning has shown great potential for modeling the physical dynamics of complex particle systems such as fluids.
no code implementations • 3 Jan 2022 • Shunyu Yao, RuiZhe Zhong, Yichao Yan, Guangtao Zhai, Xiaokang Yang
Specifically, neural radiance field takes lip movements features and personalized attributes as two disentangled conditions, where lip movements are directly predicted from the audio inputs to achieve lip-synchronized generation.
no code implementations • CVPR 2022 • Shaofeng Zhang, Lyn Qiu, Feng Zhu, Junchi Yan, Hengrui Zhang, Rui Zhao, Hongyang Li, Xiaokang Yang
Existing symmetric contrastive learning methods suffer from collapses (complete and dimensional) or quadratic complexity of objectives.
no code implementations • CVPR 2022 • Junyi Cao, Chao Ma, Taiping Yao, Shen Chen, Shouhong Ding, Xiaokang Yang
Reconstruction learning over real images enhances the learned representations to be aware of forgery patterns that are even unknown, while classification learning takes the charge of mining the essential discrepancy between real and fake images, facilitating the understanding of forgeries.
no code implementations • CVPR 2022 • Jun Jia, Zhongpai Gao, Dandan Zhu, Xiongkuo Min, Guangtao Zhai, Xiaokang Yang
In addition, the automatic localization of hidden codes significantly reduces the time of manually correcting geometric distortions for photos, which is a revolutionary innovation for information hiding in mobile applications.
no code implementations • 28 Dec 2021 • Han Lu, Zenan Li, Runzhong Wang, Qibing Ren, Junchi Yan, Xiaokang Yang
Solving combinatorial optimization (CO) on graphs is among the fundamental tasks for upper-stream applications in data mining, machine learning and operations research.
1 code implementation • 8 Dec 2021 • Wendong Zhang, Yunbo Wang, Junwei Zhu, Ying Tai, Bingbing Ni, Xiaokang Yang
We train the prior learner and the image generator as a unified model without any post-processing.
no code implementations • 29 Nov 2021 • Yichao Yan, Junjie Li, Shengcai Liao, Jie Qin, Bingbing Ni, Xiaokang Yang
In the meantime, we design an adaptive BN layer in the domain-invariant stream, to approximate the statistics of various unseen domains.
Domain Generalization
Generalizable Person Re-identification
no code implementations • 24 Nov 2021 • Jiazhong Cen, Zenkun Jiang, Lingxi Xie, Qi Tian, Xiaokang Yang, Wei Shen
Anomaly segmentation is a crucial task for safety-critical applications, such as autonomous driving in urban scenes, where the goal is to detect out-of-distribution (OOD) objects with categories which are unseen during training.
Ranked #6 on
Anomaly Detection
on Fishyscapes L&F
1 code implementation • 7 Nov 2021 • Shanyan Guan, Jingwei Xu, Michelle Z. He, Yunbo Wang, Bingbing Ni, Xiaokang Yang
We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affected by the distribution shift represented by different camera parameters, bone lengths, backgrounds, and occlusions.
Ranked #1 on
3D Absolute Human Pose Estimation
on Surreal
no code implementations • 10 Oct 2021 • Xiaoxing Wang, Wenxuan Guo, Junchi Yan, Jianlin Su, Xiaokang Yang
Also, we search on the search space of DARTS to compare with peer methods, and our discovered architecture achieves 97. 54% accuracy on CIFAR-10 and 75. 7% top-1 accuracy on ImageNet, which are state-of-the-art performance.
no code implementations • 30 Sep 2021 • Xiaoxing Wang, Xiangxiang Chu, Junchi Yan, Xiaokang Yang
Neural architecture search (NAS) has been an active direction of automatic machine learning (Auto-ML), aiming to explore efficient network structures.
no code implementations • 29 Sep 2021 • Shaofeng Zhang, Meng Liu, Junchi Yan, Hengrui Zhang, Lingxiao Huang, Pinyan Lu, Xiaokang Yang
Negative pairs are essential in contrastive learning, which plays the role of avoiding degenerate solutions.
no code implementations • ICLR 2022 • Shaofeng Zhang, Feng Zhu, Junchi Yan, Rui Zhao, Xiaokang Yang
The proposed two methods (FCL, ICL) can be combined synthetically, called Zero-CL, where ``Zero'' means negative samples are \textbf{zero} relevant, which allows Zero-CL to completely discard negative pairs i. e., with \textbf{zero} negative samples.
no code implementations • 29 Sep 2021 • Runzhong Wang, Li Shen, Yiting Chen, Junchi Yan, Xiaokang Yang, DaCheng Tao
Cardinality constrained combinatorial optimization requires selecting an optimal subset of $k$ elements, and it will be appealing to design data-driven algorithms that perform TopK selection over a probability distribution predicted by a neural network.
1 code implementation • 1 Sep 2021 • Yichao Yan, Jinpeng Li, Jie Qin, Shengcai Liao, Xiaokang Yang
Third, by investigating the advantages of both anchor-based and anchor-free models, we further augment AlignPS with an ROI-Align head, which significantly improves the robustness of re-id features while still keeping our model highly efficient.
Ranked #3 on
Person Search
on PRW
1 code implementation • ICCV 2021 • Jilai Zheng, Chao Ma, Houwen Peng, Xiaokang Yang
In this paper, we propose to learn an Unsupervised Single Object Tracker (USOT) from scratch.
no code implementations • 28 Jul 2021 • Weixia Zhang, Kede Ma, Guangtao Zhai, Xiaokang Yang
In this paper, we present a simple yet effective continual learning method for BIQA with improved quality prediction accuracy, plasticity-stability trade-off, and task-order/length robustness.
no code implementations • 27 Jul 2021 • Hang Liu, Menghan Hu, Yuzhen Chen, Qingli Li, Guangtao Zhai, Simon X. Yang, Xiao-Ping Zhang, Xiaokang Yang
This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands.
no code implementations • 10 Jul 2021 • Jinpeng Li, Yichao Yan, Shengcai Liao, Xiaokang Yang, Ling Shao
Transformers have demonstrated great potential in computer vision tasks.
no code implementations • CVPR 2021 • Chunwei Wang, Chao Ma, Ming Zhu, Xiaokang Yang
On one hand, PointAugmenting decorates point clouds with corresponding point-wise CNN features extracted by pretrained 2D detection models, and then performs 3D object detection over the decorated point clouds.
1 code implementation • 19 Jun 2021 • Yichao Yan, Jinpeng Li, Shengcai Liao, Jie Qin, Bingbing Ni, Xiaokang Yang, Ling Shao
This paper inventively considers weakly supervised person search with only bounding box annotations.
1 code implementation • 14 Jun 2021 • Wendong Zhang, Junwei Zhu, Ying Tai, Yunbo Wang, Wenqing Chu, Bingbing Ni, Chengjie Wang, Xiaokang Yang
Based on the semantic priors, we further propose a context-aware image inpainting model, which adaptively integrates global semantics and local features in a unified image generator.
1 code implementation • NeurIPS 2021 • Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang
Combinatorial Optimization (CO) has been a long-standing challenging research topic featured by its NP-hard nature.
no code implementations • 5 Jun 2021 • Yilin Wang, Shaozuo Yu, Xiaokang Yang, Wei Shen
In this paper, we propose a generic model transfer scheme to make Convlutional Neural Networks (CNNs) interpretable, while maintaining their high classification accuracy.
1 code implementation • AAAI 2021 • Chao Chen, Dongsheng Li, Junchi Yan, Hanchi Huang, Xiaokang Yang
One-bit matrix completion is an important class of positiveunlabeled (PU) learning problems where the observations consist of only positive examples, eg, in top-N recommender systems.
1 code implementation • 29 Apr 2021 • Yichao Yan, Jie Qin, Bingbing Ni, Jiaxin Chen, Li Liu, Fan Zhu, Wei-Shi Zheng, Xiaokang Yang, Ling Shao
Extensive experiments on the novel dataset as well as three existing datasets clearly demonstrate the effectiveness of the proposed framework for both group-based re-id tasks.
1 code implementation • CVPR 2021 • Shanyan Guan, Jingwei Xu, Yunbo Wang, Bingbing Ni, Xiaokang Yang
This paper considers a new problem of adapting a pre-trained model of human mesh reconstruction to out-of-domain streaming videos.
Ranked #16 on
3D Human Pose Estimation
on 3DPW
1 code implementation • CVPR 2021 • Shuai Jia, Yibing Song, Chao Ma, Xiaokang Yang
Recently, adversarial attack has been applied to visual object tracking to evaluate the robustness of deep trackers.
no code implementations • 23 Mar 2021 • Mingyu Wu, Boyuan Jiang, Donghao Luo, Junchi Yan, Yabiao Wang, Ying Tai, Chengjie Wang, Jilin Li, Feiyue Huang, Xiaokang Yang
For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame.
1 code implementation • 19 Feb 2021 • Weixia Zhang, Dingquan Li, Chao Ma, Guangtao Zhai, Xiaokang Yang, Kede Ma
In this paper, we formulate continual learning for BIQA, where a model learns continually from a stream of IQA datasets, building on what was learned from previously seen data.
no code implementations • 31 Jan 2021 • Longyuan Li, Junchi Yan, Xiaokang Yang, Yaohui Jin
We propose a deep state space model for probabilistic time series forecasting whereby the non-linear emission model and transition model are parameterized by networks and the dependency is modeled by recurrent neural nets.
no code implementations • 1 Jan 2021 • Shaofeng Zhang, Junchi Yan, Xiaokang Yang
Despite their success in perception over the last decade, deep neural networks are also known ravenous to labeled data for training, which limits their applicability to real-world problems.
no code implementations • 1 Jan 2021 • Duo Li, Sanli Tang, Zhanzhan Cheng, ShiLiang Pu, Yi Niu, Wenming Tan, Fei Wu, Xiaokang Yang
However, the impact of the pseudo-labeled samples' quality as well as the mining strategies for high quality training sample have rarely been studied in SSL.
1 code implementation • NeurIPS 2020 • Runzhong Wang, Junchi Yan, Xiaokang Yang
This paper considers the setting of jointly matching and clustering multiple graphs belonging to different groups, which naturally rises in many realistic problems.
Ranked #2 on
Graph Matching
on Willow Object Class
no code implementations • CVPR 2021 • Runzhong Wang, Tianqi Zhang, Tianshu Yu, Junchi Yan, Xiaokang Yang
This paper presents a hybrid approach by combing the interpretability of traditional search-based techniques for producing the edit path, as well as the efficiency and adaptivity of deep embedding models to achieve a cost-effective GED solver.
no code implementations • 23 Nov 2020 • Xiaoxing Wang, Xiangxiang Chu, Yuda Fan, Zhexi Zhang, Xiaolin Wei, Junchi Yan, Xiaokang Yang
Single-path based differentiable neural architecture search has great strengths for its low computational cost and memory-friendly nature.
no code implementations • 22 Nov 2020 • Weixia Zhang, Chao Ma, Qi Wu, Xiaokang Yang
We then propose to recursively alternate the learning schemes of imitation and exploration to narrow the discrepancy between training and inference.
no code implementations • ECCV 2020 • Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Xiaolong Wang, Trevor Darrell
Generating diverse and natural human motion is one of the long-standing goals for creating intelligent characters in the animated world.
no code implementations • 16 Aug 2020 • Ming Zhu, Chao Ma, Pan Ji, Xiaokang Yang
In this paper, we focus on exploring the fusion of images and point clouds for 3D object detection in view of the complementary nature of the two modalities, i. e., images possess more semantic information while point clouds specialize in distance sensing.
1 code implementation • ECCV 2020 • Shuai Jia, Chao Ma, Yibing Song, Xiaokang Yang
On one hand, we add the temporal perturbations into the original video sequences as adversarial examples to greatly degrade the tracking performance.
1 code implementation • ECCV 2020 • Ruixue Tang, Chao Ma, Wei Emma Zhang, Qi Wu, Xiaokang Yang
However, there are few works studying the data augmentation problem for VQA and none of the existing image based augmentation schemes (such as rotation and flipping) can be directly applied to VQA due to its semantic structure -- an $\langle image, question, answer\rangle$ triplet needs to be maintained correctly.
no code implementations • 3 Jul 2020 • Shanyan Guan, Ying Tai, Bingbing Ni, Feida Zhu, Feiyue Huang, Xiaokang Yang
The latent code of the recent popular model StyleGAN has learned disentangled representations thanks to the multi-layer style-based generator.
1 code implementation • ICML 2020 • Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Trevor Darrell
In video prediction tasks, one major challenge is to capture the multi-modal nature of future contents and dynamics.
1 code implementation • 28 May 2020 • Weixia Zhang, Kede Ma, Guangtao Zhai, Xiaokang Yang
Nevertheless, due to the distributional shift between images simulated in the laboratory and captured in the wild, models trained on databases with synthetic distortions remain particularly weak at handling realistic distortions (and vice versa).
1 code implementation • 27 May 2020 • Zhongpai Gao, Guangtao Zhai, Junchi Yan, Xiaokang Yang
Various point neural networks have been developed with isotropic filters or using weighting matrices to overcome the structure inconsistency on point clouds.
5 code implementations • 28 Apr 2020 • Xue Yang, Junchi Yan, Wenlong Liao, Xiaokang Yang, Jin Tang, Tao He
Instance-level denoising on the feature map is performed to enhance the detection to small and cluttered objects.
Ranked #26 on
Object Detection In Aerial Images
on DOTA
1 code implementation • 21 Apr 2020 • Zhongpai Gao, Junchi Yan, Guangtao Zhai, Juyong Zhang, Yiyan Yang, Xiaokang Yang
Mesh is a powerful data structure for 3D shapes.
no code implementations • 12 Dec 2019 • Yucheng Zhu, Xiongkuo Min, Dandan Zhu, Ke Gu, Jiantao Zhou, Guangtao Zhai, Xiaokang Yang, Wenjun Zhang
The saliency annotations of head and eye movements for both original and augmented videos are collected and together constitute the ARVR dataset.
no code implementations • 3 Dec 2019 • Jun Jia, Zhongpai Gao, Kang Chen, Menghan Hu, Guangtao Zhai, Guodong Guo, Xiaokang Yang
To train a robust decoder against the physical distortion from the real world, a distortion network based on 3D rendering is inserted between the encoder and the decoder to simulate the camera imaging process.
1 code implementation • 26 Nov 2019 • Runzhong Wang, Junchi Yan, Xiaokang Yang
We also show how to extend our network to hypergraph matching, and matching of multiple graphs.
Ranked #3 on
Graph Matching
on SPair-71k
no code implementations • 21 Nov 2019 • Zhijie Chen, Junchi Yan, Longyuan Li, Xiaokang Yang
Our model is aimed to reconstruct neuron information while inferring representations of neuron spiking states.
no code implementations • 19 Nov 2019 • Dandan Zhu, Tian Han, Linqi Zhou, Xiaokang Yang, Ying Nian Wu
We propose the clustered generator model for clustering which contains both continuous and discrete latent variables.
no code implementations • 25 Sep 2019 • Jingwei Xu, Huazhe Xu, Bingbing Ni, Xiaokang Yang, Trevor Darrell
Learning diverse and natural behaviors is one of the longstanding goal for creating intelligent characters in the animated world.
no code implementations • 25 Sep 2019 • Zhongpai Gao, Juyong Zhang, Yudong Guo, Chao Ma, Guangtao Zhai, Xiaokang Yang
Moreover, the identity and expression representations are entangled in these models, which hurdles many facial editing applications.
1 code implementation • 1 Jul 2019 • Weixia Zhang, Kede Ma, Guangtao Zhai, Xiaokang Yang
Computational models for blind image quality assessment (BIQA) are typically trained in well-controlled laboratory environments with limited generalizability to realistically distorted images.
no code implementations • 29 May 2019 • Weichang Wu, Junchi Yan, Xiaokang Yang, Hongyuan Zha
Temporal point process is an expressive tool for modeling event sequences over time.
2 code implementations • 4 Apr 2019 • Xinyuan Chen, Chang Xu, Xiaokang Yang, Li Song, DaCheng Tao
We propose adversarial gated networks (Gated GAN) to transfer multiple styles in a single model.
no code implementations • CVPR 2019 • Yichao Yan, Qiang Zhang, Bingbing Ni, Wendong Zhang, Minghao Xu, Xiaokang Yang
Person re-identification has achieved great progress with deep convolutional neural networks.
1 code implementation • ICCV 2019 • Runzhong Wang, Junchi Yan, Xiaokang Yang
In addition with its NP-completeness nature, another important challenge is effective modeling of the node-wise and structure-wise affinity across graphs and the resulting objective, to guide the matching procedure effectively finding the true matching against noises.
1 code implementation • NeurIPS 2018 • Jingwei Xu, Bingbing Ni, Xiaokang Yang
Most adversarial learning based video prediction methods suffer from image blur, since the commonly used adversarial and regression loss pair work rather in a competitive way than collaboration, yielding compromised blur effect.
no code implementations • 30 Sep 2018 • Zichuan Liu, Guosheng Lin, Wang Ling Goh, Fayao Liu, Chunhua Shen, Xiaokang Yang
In this work, we propose a novel hybrid method for scene text detection namely Correlation Propagation Network (CPN).
1 code implementation • ECCV 2018 • Xiankai Lu, Chao Ma, Bingbing Ni, Xiaokang Yang, Ian Reid, Ming-Hsuan Yang
Regression trackers directly learn a mapping from regularly dense samples of target objects to soft labels, which are usually generated by a Gaussian function, to estimate target positions.
no code implementations • CVPR 2018 • Huanyu Yu, Shuo Cheng, Bingbing Ni, Minsi Wang, Jian Zhang, Xiaokang Yang
First, to facilitate this novel research of fine-grained video caption, we collected a novel dataset called Fine-grained Sports Narrative dataset (FSN) that contains 2K sports videos with ground-truth narratives from YouTube. com.
1 code implementation • CVPR 2018 • Zan Shen, Yi Xu, Bingbing Ni, Minsi Wang, Jianguo Hu, Xiaokang Yang
Crowd counting or density estimation is a challenging task in computer vision due to large scale variations, perspective distortions and serious occlusions, etc.
Ranked #4 on
Crowd Counting
on WorldExpo’10
no code implementations • CVPR 2018 • Jingwei Xu, Bingbing Ni, Zefan Li, Shuo Cheng, Xiaokang Yang
Despite recent emergence of adversarial based methods for video prediction, existing algorithms often produce unsatisfied results in image regions with rich structural information (i. e., object boundary) and detailed motion (i. e., articulated body movement).
no code implementations • CVPR 2018 • Taiping Yao, Minsi Wang, Bingbing Ni, Huawei Wei, Xiaokang Yang
Most human activity analysis works (i. e., recognition orãprediction) only focus on a single granularity, i. e., eitherãmodelling global motion based on the coarse level movement such as human trajectories orãforecasting future detailed action based on body partsâ movement such as skeleton motion.
no code implementations • ECCV 2018 • Xinyuan Chen, Chang Xu, Xiaokang Yang, DaCheng Tao
This paper studies the object transfiguration problem in wild images.
no code implementations • 21 Jan 2018 • Weichang Wu, Junchi Yan, Xiaokang Yang, Hongyuan Zha
In conventional (multi-dimensional) marked temporal point process models, event is often encoded by a single discrete variable i. e. a marker.
no code implementations • ICCV 2017 • Zefan Li, Bingbing Ni, Wenjun Zhang, Xiaokang Yang, Wen Gao
Input binarization has shown to be an effective way for network acceleration.
no code implementations • 12 Jul 2017 • Menghan Hu, Xiongkuo Min, Guangtao Zhai, Wenhan Zhu, Yucheng Zhu, Zhaodi Wang, Xiaokang Yang, Guang Tian
Subsequently, the existing no-reference IQA algorithms, which were 5 opinion-aware approaches viz., NFERM, GMLF, DIIVINE, BRISQUE and BLIINDS2, and 8 opinion-unaware approaches viz., QAC, SISBLIM, NIQE, FISBLIM, CPBD, S3 and Fish_bb, were executed for the evaluation of the THz security image quality.
1 code implementation • 12 Jul 2017 • Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang
Specifically, we learn adaptive correlation filters on the outputs from each convolutional layer to encode the target appearance.
1 code implementation • 7 Jul 2017 • Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang
Second, we learn a correlation filter over a feature pyramid centered at the estimated target position for predicting scale changes.
no code implementations • 4 Jul 2017 • Yichao Yan, Jingwei Xu, Bingbing Ni, Xiaokang Yang
This work make the first attempt to generate articulated human motion sequence from a single image.
Ranked #2 on
Gesture-to-Gesture Translation
on NTU Hand Digit
no code implementations • CVPR 2017 • Rui Yang, Bingbing Ni, Chao Ma, Yi Xu, Xiaokang Yang
We introduce a Multiple Granularity Analysis framework for video segmentation in a coarse-to-fine manner.
no code implementations • CVPR 2017 • Minsi Wang, Bingbing Ni, Xiaokang Yang
However, most of the previous activity recognition methods do not offer a flexible and scalable scheme to handle the high order context modeling problem.
no code implementations • 10 Jun 2017 • Donghao Luo, Bingbing Ni, Yichao Yan, Xiaokang Yang
Towards this end, we propose a novel loopy recurrent neural network (Loopy RNN), which is capable of aggregating relationship information of two input images in a progressive/iterative manner and outputting the consolidated matching score in the final iteration.
no code implementations • 1 Jun 2017 • Wendong Zhang, Bingbing Ni, Yichao Yan, Jingwei Xu, Xiaokang Yang
Key to automatically generate natural scene images is to properly arrange among various spatial elements, especially in the depth direction.
no code implementations • 26 May 2017 • Yichao Yan, Bingbing Ni, Xiaokang Yang
Predicting human interaction is challenging as the on-going activity has to be inferred based on a partially observed video.
2 code implementations • 24 May 2017 • Shuai Xiao, Junchi Yan, Stephen M. Chu, Xiaokang Yang, Hongyuan Zha
In this paper, we model the background by a Recurrent Neural Network (RNN) with its units aligned with time series indexes while the history effect is modeled by another RNN whose units are aligned with asynchronous events to capture the long-range dynamics.
no code implementations • 24 Mar 2017 • Shuai Xiao, Junchi Yan, Mehrdad Farajtabar, Le Song, Xiaokang Yang, Hongyuan Zha
A variety of real-world processes (over networks) produce sequences of data whose complex temporal dynamics need to be studied.
1 code implementation • 23 Jan 2017 • Yichao Yan, Bingbing Ni, Zhichao Song, Chao Ma, Yan Yan, Xiaokang Yang
We address the person re-identification problem by effectively exploiting a globally discriminative feature representation from a sequence of tracked human regions/patches.
2 code implementations • 18 Dec 2016 • Chao Ma, Chih-Yuan Yang, Xiaokang Yang, Ming-Hsuan Yang
Numerous single-image super-resolution algorithms have been proposed in the literature, but few studies address the problem of performance evaluation based on visual perception.
no code implementations • CVPR 2016 • Wanli Ouyang, Xiaogang Wang, Cong Zhang, Xiaokang Yang
Our analysis and empirical results show that classes with more samples have higher impact on the feature learning.
no code implementations • CVPR 2016 • Bingbing Ni, Xiaokang Yang, Shenghua Gao
Fine grained video action analysis often requires reliable detection and tracking of various interacting objects and human body parts, denoted as interactional object parsing.
no code implementations • CVPR 2016 • Jun Yuan, Bingbing Ni, Xiaokang Yang, Ashraf A. Kassim
We investigate the feature design and classification architectures in temporal action localization.
no code implementations • CVPR 2016 • Yang Zhou, Bingbing Ni, Richang Hong, Xiaokang Yang, Qi Tian
Firstly, a novel EM-like learning framework is proposed to train the pixel-level deep convolutional neural network (DCNN) by seamlessly integrating weakly supervised data (i. e., massive bounding box annotations) with a small set of strongly supervised data (i. e., fully annotated hand segmentation maps) to achieve state-of-the-art hand segmentation performance.
no code implementations • 20 Jan 2016 • Wanli Ouyang, Xiaogang Wang, Cong Zhang, Xiaokang Yang
Our analysis and empirical results show that classes with more samples have higher impact on the feature learning.
no code implementations • ICCV 2015 • Junchi Yan, Hongteng Xu, Hongyuan Zha, Xiaokang Yang, Huanxi Liu, Stephen Chu
Graph matching has a wide spectrum of real-world applications and in general is known NP-hard.
no code implementations • ICCV 2015 • Chao Ma, Jia-Bin Huang, Xiaokang Yang, Ming-Hsuan Yang
The outputs of the last convolutional layers encode the semantic information of targets and such representations are robust to significant appearance variations.
no code implementations • CVPR 2015 • Cong Zhang, Hongsheng Li, Xiaogang Wang, Xiaokang Yang
To address this problem, we propose a deep convolutional neural network (CNN) for crowd counting, and it is trained alternatively with two related learning objectives, crowd density and crowd count.
Ranked #15 on
Crowd Counting
on WorldExpo’10
no code implementations • CVPR 2015 • Junchi Yan, Chao Zhang, Hongyuan Zha, Wei Liu, Xiaokang Yang, Stephen M. Chu
Evaluations on both synthetic and real-world data corroborate the efficiency of our method.
no code implementations • CVPR 2015 • Bingbing Ni, Pierre Moulin, Xiaokang Yang, Shuicheng Yan
Inspired by the recent advance in sentence regularization for text classification, we introduce a Motion Part Regularization framework to mining discriminative semi-local groups of dense trajectories.
no code implementations • CVPR 2015 • Chao Ma, Xiaokang Yang, Chongyang Zhang, Ming-Hsuan Yang
In this paper, we address the problem of long-term visual tracking where the target objects undergo significant appearance variation due to deformation, abrupt motion, heavy occlusion and out-of-the-view.
no code implementations • 20 Feb 2015 • Junchi Yan, Minsu Cho, Hongyuan Zha, Xiaokang Yang, Stephen Chu
We propose multi-graph matching methods to incorporate the two aspects by boosting the affinity score, meanwhile gradually infusing the consistency as a regularizer.