no code implementations • ECCV 2020 • Jibin Gao, Wei-Shi Zheng, Jia-Hui Pan, Chengying Gao, Yao-Wei Wang, Wei Zeng, Jian-Huang Lai
However, existing methods for action assessment are mostly limited to individual actions, especially lacking modeling of the asymmetric relations among agents (e. g., between persons and objects); and this limitation undermines their ability to assess actions containing asymmetrically interactive motion patterns, since there always exists subordination between agents in many interactive actions.
no code implementations • 11 May 2023 • Qing Zhang, Hao Jiang, Yongwei Nie, Wei-Shi Zheng
We present a simple but effective technique to smooth out textures while preserving the prominent structures.
no code implementations • 18 Apr 2023 • Wentao Zhang, Yujun Huang, Tong Zhang, Qingsong Zou, Wei-Shi Zheng, Ruixuan Wang
To address the catastrophic forgetting issue, a novel adapter-based strategy is proposed to help effectively learn a set of new diseases at each round (or task) of continual learning, without changing the shared feature extractor.
1 code implementation • CVPR 2023 • Jiawei Feng, AnCong Wu, Wei-Shi Zheng
To this end, we propose shape-erased feature learning paradigm that decorrelates modality-shared features in two orthogonal subspaces.
no code implementations • 7 Apr 2023 • Gaojie Wu, Wei-Shi Zheng, Yutong Lu, Qi Tian
In this work, we propose a ladder self-attention block with multiple branches and a progressive shift mechanism to develop a light-weight transformer backbone that requires less computing resources (e. g. a relatively small number of parameters and FLOPs), termed Progressive Shift Ladder Transformer (PSLT).
1 code implementation • 3 Feb 2023 • Jiayu Jiao, Yu-Ming Tang, Kun-Yu Lin, Yipeng Gao, Jinhua Ma, YaoWei Wang, Wei-Shi Zheng
In this work, we explore effective Vision Transformers to pursue a preferable trade-off between the computational complexity and size of the attended receptive field.
no code implementations • 18 Jan 2023 • Kanghao Chen, Sijia Liu, Ruixuan Wang, Wei-Shi Zheng
The first one is to adaptively integrate multiple levels of old knowledge and transfer it to each block level in the new model.
no code implementations • CVPR 2023 • Chaolei Tan, Zihang Lin, Jian-Fang Hu, Wei-Shi Zheng, JianHuang Lai
Specifically, we develop a hierarchical encoder that encodes the multi-modal inputs into semantics-aligned representations at different levels.
no code implementations • CVPR 2023 • Zuhao Liu, Xiao-Ming Wu, Dian Zheng, Kun-Yu Lin, Wei-Shi Zheng
There also exists a scene gap between virtual and real scenarios, including scene-specific anomalies (events that are abnormal in one scene but normal in another) and scene-specific attributes, such as the viewpoint of the surveillance camera.
Anomaly Detection In Surveillance Videos Video Anomaly Detection
no code implementations • CVPR 2023 • Zihang Lin, Chaolei Tan, Jian-Fang Hu, Zhi Jin, Tiancai Ye, Wei-Shi Zheng
The static stream performs cross-modal understanding in a single frame and learns to attend to the target object spatially according to intra-frame visual cues like object appearances.
1 code implementation • CVPR 2023 • Yipeng Gao, Kun-Yu Lin, Junkai Yan, YaoWei Wang, Wei-Shi Zheng
Critically, in FSDAOD, the data-scarcity in the target domain leads to an extreme data imbalance between the source and target domains, which potentially causes over-adaptation in traditional feature alignment.
no code implementations • 27 Sep 2022 • Chengzhi Lin, AnCong Wu, Junwei Liang, Jun Zhang, Wenhang Ge, Wei-Shi Zheng, Chunhua Shen
To address this problem, we propose a Text-Adaptive Multiple Visual Prototype Matching model, which automatically captures multiple prototypes to describe a video by adaptive aggregation of video token features.
1 code implementation • 22 Sep 2022 • Yipeng Gao, Lingxiao Yang, Yunmu Huang, Song Xie, Shiyong Li, Wei-Shi Zheng
Under the domain shift, cross-domain few-shot object detection aims to adapt object detectors in the target domain with a few annotated target data.
no code implementations • 14 Jul 2022 • Chenghua Zeng, Huijuan Lu, Kanghao Chen, Ruixuan Wang, Wei-Shi Zheng
Data imbalance between common and rare diseases during model training often causes intelligent diagnosis systems to have biased predictions towards common diseases.
no code implementations • 11 Jul 2022 • Kanghao Chen, Weixian Lei, Rong Zhang, Shen Zhao, Wei-Shi Zheng, Ruixuan Wang
For the class-center involved triplet loss, the positive and negative samples in each triplet are replaced by their corresponding class centers, which enforces data representations of the same class closer to the class center.
no code implementations • 6 Jul 2022 • Zihang Lin, Chaolei Tan, Jian-Fang Hu, Zhi Jin, Tiancai Ye, Wei-Shi Zheng
The static branch performs cross-modal understanding in a single frame and learns to localize the target object spatially according to intra-frame visual cues like object appearances.
Ranked #1 on Spatio-Temporal Video Grounding on HC-STVG2
1 code implementation • 4 Jul 2022 • Yaojia Zheng, Zhouwu Liu, Rong Mo, Ziyi Chen, Wei-Shi Zheng, Ruixuan Wang
Compared to supervised learning with labelled disease EEG data which can train a model to analyze specific diseases but would fail to monitor previously unseen statuses, anomaly detection based on only normal EEGs can detect any potential anomaly in new EEGs.
no code implementations • 22 Jun 2022 • Jia-Run Du, Jia-Chang Feng, Kun-Yu Lin, Fa-Ting Hong, Xiao-Ming Wu, Zhongang Qi, Ying Shan, Wei-Shi Zheng
Accordingly, we first exclude these surely non-existent categories by a complementary learning loss.
1 code implementation • 19 Jun 2022 • Jianxiong Tang, JianHuang Lai, Xiaohua Xie, Lingxiao Yang, Wei-Shi Zheng
The SNN2ANN consists of 2 components: a) a weight sharing architecture between ANN and SNN and b) spiking mapping units.
no code implementations • 28 Apr 2022 • Yang Yang, Zhiying Cui, Junjie Xu, Changhong Zhong, Wei-Shi Zheng, Ruixuan Wang
In this case, updating the intelligent system with data of new diseases would inevitably downgrade its performance on previously learned diseases.
1 code implementation • 27 Apr 2022 • Xin Zhang, Xiaohua Xie, JianHuang Lai, Wei-Shi Zheng
To address this issue, we propose a pedestrian retrieval framework based on cross-camera trajectory generation, which integrates both temporal and spatial information.
1 code implementation • CVPR 2022 • Yu-Ming Tang, Yi-Xing Peng, Wei-Shi Zheng
The diverse generated samples could effectively prevent DNN from forgetting when learning new tasks.
1 code implementation • CVPR 2022 • Hanjun Li, Xingjia Pan, Ke Yan, Fan Tang, Wei-Shi Zheng
Object detection under imperfect data receives great attention recently.
no code implementations • 7 Mar 2022 • Peipei Zhu, Xiao Wang, Yong Luo, Zhenglong Sun, Wei-Shi Zheng, YaoWei Wang, Changwen Chen
The image-level labels are utilized to train a weakly-supervised object recognition model to extract object information (e. g., instance) in an image, and the extracted instances are adopted to infer the relationships among different objects based on an enhanced graph neural network (GNN).
no code implementations • CVPR 2022 • Angchi Xu, Ling-An Zeng, Wei-Shi Zheng
Long-term action quality assessment is a task of evaluating how well an action is performed, namely, estimating a quality score from a long video.
Ranked #1 on Action Quality Assessment on Rhythmic Gymnastic
no code implementations • 6 Dec 2021 • Zelin Chen, Hong-Xing Yu, AnCong Wu, Wei-Shi Zheng
To make the application of writer-id more practical (e. g., on mobile devices), we focus on a novel problem, letter-level online writer-id, which requires only a few trajectories of written letters as identification cues.
no code implementations • NeurIPS 2021 • Jiangxin Sun, Zihang Lin, Xintong Han, Jian-Fang Hu, Jia Xu, Wei-Shi Zheng
The ability of forecasting future human motion is important for human-machine interaction systems to understand human behaviors and make interaction.
1 code implementation • 25 Aug 2021 • Jia-Xin Zhuang, Wanying Tao, Jianfei Xing, Wei Shi, Ruixuan Wang, Wei-Shi Zheng
In this paper, a simple yet effective optimization method is proposed to interpret the activation of any kernel of interest in CNN models.
no code implementations • 11 Aug 2021 • Changhong Zhong, Zhiying Cui, Ruixuan Wang, Wei-Shi Zheng
Successful continual learning of new knowledge would enable intelligent systems to recognize more and more classes of objects.
1 code implementation • 29 Jul 2021 • Wenhang Ge, Chunyan Pan, AnCong Wu, Hongwei Zheng, Wei-Shi Zheng
To learn camera-invariant representation from cross-camera unpaired training data, we propose a cross-camera feature prediction method to mine cross-camera self supervision information from camera-specific feature distribution by transforming fake cross-camera positive feature pairs and minimize the distances of the fake pairs.
1 code implementation • 27 Jul 2021 • Fa-Ting Hong, Jia-Chang Feng, Dan Xu, Ying Shan, Wei-Shi Zheng
In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.
Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1
1 code implementation • Proceedings of the 29th ACM International Conference on Multimedia 2021 • Fa-Ting Hong, Jia-Chang Feng, Dan Xu, Ying Shan, Wei-Shi Zheng
In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.
Weakly-supervised Temporal Action Localization Weakly Supervised Temporal Action Localization
1 code implementation • 20 Jul 2021 • ShaoHao Lu, Yuqiao Xian, Ke Yan, Yi Hu, Xing Sun, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng
The Deep Neural Networks are vulnerable toadversarial exam-ples(Figure 1), making the DNNs-based systems collapsed byadding the inconspicuous perturbations to the images.
no code implementations • 20 Jun 2021 • Chaolei Tan, Zihang Lin, Jian-Fang Hu, Xiang Li, Wei-Shi Zheng
We propose an effective two-stage approach to tackle the problem of language-based Human-centric Spatio-Temporal Video Grounding (HC-STVG) task.
no code implementations • CVPR 2021 • Jiaming Zhou, Kun-Yu Lin, Haoxin Li, Wei-Shi Zheng
In this paper, we propose a Graph-based High-order Relation Modeling (GHRM) module to exploit the high-order relations in the long-term actions for long-term action recognition.
no code implementations • CVPR 2021 • Peixian Hong, Tao Wu, AnCong Wu, Xintong Han, Wei-Shi Zheng
Recently, person re-identification (Re-ID) has achieved great progress.
Ranked #3 on Person Re-Identification on PRCC
1 code implementation • CVPR 2021 • Jiaxing Chen, Xinyang Jiang, Fudong Wang, Jun Zhang, Feng Zheng, Xing Sun, Wei-Shi Zheng
In this paper, rather than relying on texture based information, we propose to improve the robustness of person ReID against clothing texture by exploiting the information of a person's 3D shape.
Ranked #4 on Person Re-Identification on PRCC
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.
no code implementations • 28 Apr 2021 • Zhuoyun Li, Changhong Zhong, Sijia Liu, Ruixuan Wang, Wei-Shi Zheng
In order to reduce the forgetting of particularly earlier learned old knowledge and improve the overall continual learning performance, we propose a simple yet effective fusion mechanism by including all the previously learned feature extractors into the intelligent model.
1 code implementation • CVPR 2021 • Hanjun Li, Gaojie Wu, Wei-Shi Zheng
We propose a novel search space called Combined Depth Space (CDS), based on which we search for an efficient network architecture, which we call CDNet, via a differentiable architecture search algorithm.
1 code implementation • CVPR 2021 • Jia-Chang Feng, Fa-Ting Hong, Wei-Shi Zheng
Weakly supervised video anomaly detection (WS-VAD) is to distinguish anomalies from normal events based on discriminative representations.
1 code implementation • 1 Mar 2021 • Yang Yang, Jiancong Chen, Ruixuan Wang, Ting Ma, Lingwei Wang, Jie Chen, Wei-Shi Zheng, Tong Zhang
Despite tremendous efforts, it is very challenging to generate a robust model to assist in the accurate quantification assessment of COVID-19 on chest CT images.
no code implementations • ICCV 2021 • Jinrui Yang, Jiawei Zhang, Fufu Yu, Xinyang Jiang, Mengdan Zhang, Xing Sun, Ying-Cong Chen, Wei-Shi Zheng
Several mainstream methods utilize extra cues (e. g., human pose information) to distinguish human parts from obstacles to alleviate the occlusion problem.
no code implementations • ICCV 2021 • Zihang Lin, Jiangxin Sun, Jian-Fang Hu, QiZhi Yu, Jian-Huang Lai, Wei-Shi Zheng
In the latent feature learned by the autoencoder, global structures are enhanced and local details are suppressed so that it is more predictive.
1 code implementation • ICCV 2021 • Shizhen Zhao, Changxin Gao, Yuanjie Shao, Wei-Shi Zheng, Nong Sang
Specifically, to alleviate the intra-class variations, a clustering method is utilized to generate pseudo labels for both visual and textual instances.
1 code implementation • 10 Dec 2020 • Enwei Zhang, Xinyang Jiang, Hao Cheng, AnCong Wu, Fufu Yu, Ke Li, Xiaowei Guo, Feng Zheng, Wei-Shi Zheng, Xing Sun
Current training objectives of existing person Re-IDentification (ReID) models only ensure that the loss of the model decreases on selected training batch, with no regards to the performance on samples outside the batch.
no code implementations • ECCV 2020 • Hai Wang, Wei-Shi Zheng, Ling Yingbiao
However, previous graph models regard human and object as the same kind of nodes and do not consider that the messages are not equally the same between different entities.
1 code implementation • 11 Sep 2020 • Fufu Yu, Xinyang Jiang, Yifei Gong, Shizhen Zhao, Xiaowei Guo, Wei-Shi Zheng, Feng Zheng, Xing Sun
Secondly, the Conditional Feature Embedding requires the overall feature of a query image to be dynamically adjusted based on the gallery image it matches, while most of the existing methods ignore the reference images.
Ranked #1 on Person Re-Identification on CUHK03-C
1 code implementation • ECCV 2020 • Shizhen Zhao, Changxin Gao, Jun Zhang, Hao Cheng, Chuchu Han, Xinyang Jiang, Xiaowei Guo, Wei-Shi Zheng, Nong Sang, Xing Sun
In the conventional person Re-ID setting, it is widely assumed that cropped person images are for each individual.
1 code implementation • 13 Aug 2020 • Ling-An Zeng, Fa-Ting Hong, Wei-Shi Zheng, Qi-Zhi Yu, Wei Zeng, Yao-Wei Wang, Jian-Huang Lai
However, most existing works focus only on video dynamic information (i. e., motion information) but ignore the specific postures that an athlete is performing in a video, which is important for action assessment in long videos.
Ranked #2 on Action Quality Assessment on Rhythmic Gymnastic
no code implementations • ECCV 2020 • Fa-Ting Hong, Xuanteng Huang, Wei-Hong Li, Wei-Shi Zheng
We address the weakly supervised video highlight detection problem for learning to detect segments that are more attractive in training videos given their video event label but without expensive supervision of manually annotating highlight segments.
1 code implementation • CVPR 2020 • Haoxin Li, Wei-Shi Zheng, Yu Tao, Haifeng Hu, Jian-Huang Lai
We propose to search the network structures with differentiable architecture search mechanism, which learns to construct adaptive structures for different videos to facilitate adaptive interaction modeling.
1 code implementation • CVPR 2020 • Fa-Ting Hong, Wei-Hong Li, Wei-Shi Zheng
Important people detection is to automatically detect the individuals who play the most important roles in a social event image, which requires the designed model to understand a high-level pattern.
2 code implementations • CVPR 2020 • Hong-Xing Yu, Wei-Shi Zheng
We evaluate our model on unsupervised person re-identification and pose-invariant face recognition.
1 code implementation • 6 Feb 2020 • Qize Yang, An-Cong Wu, Wei-Shi Zheng
Substantial development of re-id has recently been observed, and the majority of existing models are largely dependent on color appearance and assume that pedestrians do not change their clothes across camera views.
1 code implementation • 3 Dec 2019 • Zhihui Zhu, Xinyang Jiang, Feng Zheng, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng, Xing Sun
Instead of one subspace for each viewpoint, our method projects the feature from different viewpoints into a unified hypersphere and effectively models the feature distribution on both the identity-level and the viewpoint-level.
Ranked #6 on Person Re-Identification on Market-1501 (using extra training data)
2 code implementations • 28 Nov 2019 • Xinyang Jiang, Yifei Gong, Xiaowei Guo, Qize Yang, Feiyue Huang, Wei-Shi Zheng, Feng Zheng, Xing Sun
Recently, the research interest of person re-identification (ReID) has gradually turned to video-based methods, which acquire a person representation by aggregating frame features of an entire video.
no code implementations • 31 Oct 2019 • Zhirui Chen, Jianheng Li, Wei-Shi Zheng
The scalability problem caused by the difficulty in annotating Person Re-identification(Re-ID) datasets has become a crucial bottleneck in the development of Re-ID. To address this problem, many unsupervised Re-ID methods have recently been proposed. Nevertheless, most of these models require transfer from another auxiliary fully supervised dataset, which is still expensive to obtain. In this work, we propose a Re-ID model based on Weakly Supervised Tracklets(WST) data from various camera views, which can be inexpensively acquired by combining the fragmented tracklets of the same person in the same camera view over a period of time. We formulate our weakly supervised tracklets Re-ID model by a novel method, named deep feature-wise mutual learning(DFML), which consists of Mutual Learning on Feature Extractors (MLFE) and Mutual Learning on Feature Classifiers (MLFC). We propose MLFE by leveraging two feature extractors to learn from each other to extract more robust and discriminative features. On the other hand, we propose MLFC by adapting discriminative features from various camera views to each classifier.
2 code implementations • 30 Oct 2019 • Qing Zhang, Yongwei Nie, Wei-Shi Zheng
By performing dual illumination estimation, we obtain two intermediate exposure correction results for the input image, with one fixes the underexposed regions and the other one restores the overexposed regions.
no code implementations • 21 Oct 2019 • Jiabo Huang, Xiaohua Xie, Wei-Shi Zheng
This paper studies the problem of aligning a set of face images of the same individual into a normalized image while removing the outliers like partial occlusion, extreme facial expression as well as significant illumination variation.
no code implementations • 30 Sep 2019 • Guang-Yuan Hao, Hong-Xing Yu, Wei-Shi Zheng
We focus on explicitly learning disentangled representation for natural image generation, where the underlying spatial structure and the rendering on the structure can be independently controlled respectively, yet using no tuple supervision.
1 code implementation • CVPR 2020 • Zilong Zhong, Zhong Qiu Lin, Rene Bidart, Xiaodan Hu, Ibrahim Ben Daya, Zhifeng Li, Wei-Shi Zheng, Jonathan Li, Alexander Wong
The recent integration of attention mechanisms into segmentation networks improves their representational capabilities through a great emphasis on more informative features.
Ranked #6 on Semantic Segmentation on PASCAL VOC 2012 test
1 code implementation • 26 Jul 2019 • Shuosen Guan, Haoxin Li, Wei-Shi Zheng
Most of current Convolution Neural Network (CNN) based methods for optical flow estimation focus on learning optical flow on synthetic datasets with groundtruth, which is not practical.
no code implementations • 25 Jul 2019 • Qing Zhang, Yongwei Nie, Lei Zhu, Chunxia Xiao, Wei-Shi Zheng
To obtain high-quality results free of these artifacts, we present a novel underexposed photo enhancement approach that is able to maintain the perceptual consistency.
no code implementations • 1 Jul 2019 • Jiechao Ma, Sen Liang, Xiang Li, Hongwei Li, Bjoern H. Menze, Rongguo Zhang, Wei-Shi Zheng
Mammogram is the most effective imaging modality for the mass lesion detection of breast cancer at the early stage.
no code implementations • CVPR 2019 • Haoxin Li, Yijun Cai, Wei-Shi Zheng
To exploit the strong relations for egocentric interaction recognition, we introduce a dual relation modeling framework which learns to model the relations between the camera wearer and the interactor based on the individual action representations of the two persons.
no code implementations • 30 May 2019 • Xiang Li, Chan Lu, Danni Cheng, Wei-Hong Li, Mei Cao, Bo Liu, Jiechao Ma, Wei-Shi Zheng
Visible watermark plays an important role in image copyright protection and the robustness of a visible watermark to an attack is shown to be essential.
no code implementations • CVPR 2019 • Shuhan Tan, Jiening Jiao, Wei-Shi Zheng
Thus, it is meaningful to let partially labeled domains learn from each other to classify all the unlabeled samples in each domain under an open-set setting.
no code implementations • 24 Apr 2019 • Yanli Ji, Feixiang Xu, Yang Yang, Fumin Shen, Heng Tao Shen, Wei-Shi Zheng
Besides, we propose a View-guided Skeleton CNN (VS-CNN) to tackle the problem of arbitrary-view action recognition.
no code implementations • CVPR 2019 • Jingke Meng, Sheng Wu, Wei-Shi Zheng
In the conventional person re-id setting, it is assumed that the labeled images are the person images within the bounding box for each individual; this labeling across multiple nonoverlapping camera views from raw video surveillance is costly and time-consuming.
1 code implementation • CVPR 2019 • Wei-Hong Li, Fa-Ting Hong, Wei-Shi Zheng
In this work, we propose a deep imPOrtance relatIon NeTwork (POINT) that combines both relation modeling and feature learning.
no code implementations • 31 Mar 2019 • Hui Li, Meng Yang, Zhihui Lai, Wei-Shi Zheng, Zitong Yu
Deep part-based methods in recent literature have revealed the great potential of learning local part-level representation for pedestrian image in the task of person re-identification.
1 code implementation • CVPR 2019 • Hong-Xing Yu, Wei-Shi Zheng, An-Cong Wu, Xiaowei Guo, Shaogang Gong, Jian-Huang Lai
To overcome this problem, we propose a deep model for the soft multilabel learning for unsupervised RE-ID.
Ranked #78 on Person Re-Identification on DukeMTMC-reID
1 code implementation • 29 Jan 2019 • Hong-Xing Yu, An-Cong Wu, Wei-Shi Zheng
In such a way, DECAMEL jointly learns the feature representation and the unsupervised asymmetric metric.
no code implementations • 18 Dec 2018 • Jiechao Ma, Xiang Li, Hongwei Li, Bjoern H. Menze, Sen Liang, Rongguo Zhang, Wei-Shi Zheng
In this paper, we propose a novel and effective abnormality detector implementing the attention mechanism and group convolution on 3D single-shot detector (SSD) called group-attention SSD (GA-SSD).
Computed Tomography (CT) Finding Pulmonary Nodules In Large-Scale Ct Images
no code implementations • 3 Dec 2018 • Minghan Li, Tanli Zuo, Ruicheng Li, Martha White, Wei-Shi Zheng
Knowledge distillation is an effective technique that transfers knowledge from a large teacher model to a shallow student.
no code implementations • 19 Oct 2018 • Jiafeng Xie, Bing Shuai, Jian-Fang Hu, Jingyang Lin, Wei-Shi Zheng
Recently, segmentation neural networks have been significantly improved by demonstrating very promising accuracies on public benchmarks.
no code implementations • ECCV 2018 • Jian-Fang Hu, Wei-Shi Zheng, Jia-Hui Pan, Jian-Huang Lai, Jian-Guo Zhang
In this paper, we focus on exploring modality-temporal mutual information for RGB-D action recognition.
no code implementations • IEEE Transactions on Pattern Analysis and Machine Intelligence 2018 • Jian-Fang Hu, Wei-Shi Zheng, Lianyang Ma, Gang Wang, Jian-Huang Lai, Jian-Guo Zhang
Our formulation of soft regression framework 1) overcomes a usual assumption in existing early action prediction systems that the progress level of on-going sequence is given in the testing stage; and 2) presents a theoretical framework to better resolve the ambiguity and uncertainty of subsequences at early performing stage.
Ranked #51 on Skeleton Based Action Recognition on NTU RGB+D 120
no code implementations • ECCV 2018 • Xiang Li, An-Cong Wu, Wei-Shi Zheng
The main idea is learning to attack feature extractor on the target people by using GAN to generate very target-like images (imposters), and in the meantime the model will make the feature extractor learn to tolerate the attack by discriminative learning so as to realize group-based verification.
1 code implementation • 4 Jul 2018 • Guang-Yuan Hao, Hong-Xing Yu, Wei-Shi Zheng
In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e. g., content and style) from different domains and thus generating a new domain with learned concepts.
no code implementations • 7 May 2018 • Yongyi Tang, Lin Ma, Wei Liu, Wei-Shi Zheng
Human motion prediction aims at generating future frames of human motion based on an observed sequence of skeletons.
no code implementations • CVPR 2019 • Ganzhao Yuan, Li Shen, Wei-Shi Zheng
The sparse generalized eigenvalue problem arises in a number of standard and modern statistical learning models, including sparse principal component analysis, sparse Fisher discriminant analysis, and sparse canonical correlation analysis.
2 code implementations • 14 Feb 2018 • Hongwei Li, Gongfa Jiang, Jian-Guo Zhang, Ruixuan Wang, Zhaolei Wang, Wei-Shi Zheng, Bjoern Menze
In this paper, we present a study using deep fully convolutional network and ensemble models to automatically detect such WMH using fluid attenuation inversion recovery (FLAIR) and T1 magnetic resonance (MR) scans.
no code implementations • 5 Dec 2017 • Zhou Yin, Wei-Shi Zheng, An-Cong Wu, Hong-Xing Yu, Hai Wan, Xiaowei Guo, Feiyue Huang, Jian-Huang Lai
While attributes have been widely used for person re-identification (Re-ID) which aims at matching the same person images across disjoint camera views, they are used either as extra features or for performing multi-task learning to assist the image-image matching task.
no code implementations • 19 Nov 2017 • Ganzhao Yuan, Haoxian Tan, Wei-Shi Zheng
Sparse inverse covariance selection is a fundamental problem for analyzing dependencies in high dimensional data.
no code implementations • 9 Nov 2017 • Wei-Hong Li, Zhuowei Zhong, Wei-Shi Zheng
While there is a few work on discussing online re-id, most of them require considerable storage of all passed data samples that have been ever observed, and this could be unrealistic for processing data from a large camera network.
no code implementations • 6 Nov 2017 • Wei-Hong Li, Benchao Li, Wei-Shi Zheng
Always, some individuals in images are more important/attractive than others in some events such as presentation, basketball game or speech.
no code implementations • ICCV 2017 • Ancong Wu, Wei-Shi Zheng, Hong-Xing Yu, Shaogang Gong, Jian-Huang Lai
To that end, matching RGB images with infrared images is required, which are heterogeneous with very different visual characteristics.
Ranked #4 on Cross-Modal Person Re-Identification on SYSU-MM01 (mAP (All-search & Single-shot) metric)
Cross-Modality Person Re-identification Cross-Modal Person Re-Identification
no code implementations • 20 Sep 2017 • Yongyi Tang, Peizhen Zhang, Jian-Fang Hu, Wei-Shi Zheng
Rather than simply recognizing the action of a person individually, collective activity recognition aims to find out what a group of people is acting in a collective scene.
1 code implementation • ICCV 2017 • Hong-Xing Yu, An-Cong Wu, Wei-Shi Zheng
While metric learning is important for Person re-identification (RE-ID), a significant problem in visual surveillance for cross-view pedestrian matching, existing metric models for RE-ID are mostly based on supervised learning that requires quantities of labeled samples in all pairs of camera views for training.
Ranked #110 on Person Re-Identification on Market-1501
no code implementations • CVPR 2017 • Ganzhao Yuan, Wei-Shi Zheng, Bernard Ghanem
Incorporating a new Gaussian elimination procedure, the matrix splitting method achieves state-of-the-art performance.
no code implementations • 6 Apr 2017 • Long-Kai Huang, Qiang Yang, Wei-Shi Zheng
Specifically, a new loss function is proposed to measure the similarity loss between a pair of data samples in hamming space.
no code implementations • 28 Mar 2017 • Ancong Wu, Wei-Shi Zheng, Jian-Huang Lai
More specifically, we exploit depth voxel covariance descriptor and further propose a locally rotation invariant depth shape descriptor called Eigen-depth feature to describe pedestrian body shape.
no code implementations • 26 Mar 2017 • Ying-Cong Chen, Xiatian Zhu, Wei-Shi Zheng, Jian-Huang Lai
The challenge of person re-identification (re-id) is to match individual images of the same person captured by different non-overlapping camera views against significant and unknown cross-view feature distortion.
no code implementations • IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 39 , Issue: 11 , Nov. 1 2017 ) 2016 • Jian-Fang Hu, Wei-Shi Zheng, Jian-Huang Lai, Jian-Guo Zhang
The proposed model formed in a unified framework is capable of: 1) jointly mining a set of subspaces with the same dimensionality to exploit latent shared features across different feature channels, 2) meanwhile, quantifying the shared and feature-specific components of features in the subspaces, and 3) transferring feature-specific intermediate transforms (i-transforms) for learning fusion of heterogeneous features across datasets.
Ranked #8 on Skeleton Based Action Recognition on SYSU 3D
no code implementations • 1 Nov 2016 • Hailin Shi, Yang Yang, Xiangyu Zhu, Shengcai Liao, Zhen Lei, Wei-Shi Zheng, Stan Z. Li
From this point of view, selecting suitable positive i. e. intra-class) training samples within a local range is critical for training the CNN embedding, especially when the data has large intra-class variations.
no code implementations • CVPR 2016 • Jin-Jie You, An-Cong Wu, Xiang Li, Wei-Shi Zheng
Since only limited information can be exploited from still images, it is hard (if not impossible) to overcome the occlusion, pose and camera-view change, and lighting variation problems.
no code implementations • 26 Apr 2016 • Shangxuan Wu, Ying-Cong Chen, Xiang Li, An-Cong Wu, Jin-Jie You, Wei-Shi Zheng
In this paper, we focus on the feature representation and claim that hand-crafted histogram features can be complementary to Convolutional Neural Network (CNN) features.
no code implementations • 20 Apr 2016 • Hongwei Li, Wei-Shi Zheng, JianGuo Zhang
Automatic classification of Human Epithelial Type-2 (HEp-2) cells staining patterns is an important and yet a challenging problem.
no code implementations • ICCV 2015 • Xiang Li, Wei-Shi Zheng, Xiaojuan Wang, Tao Xiang, Shaogang Gong
In real world person re-identification (re-id), images of people captured at very different resolutions from different locations need be matched.
no code implementations • ICCV 2015 • Wei-Shi Zheng, Xiang Li, Tao Xiang, Shengcai Liao, Jian-Huang Lai, Shaogang Gong
We address a new partial person re-identification (re-id) problem, where only a partial observation of a person is available for matching across different non-overlapping camera views.
no code implementations • 1 Feb 2015 • Yuanlu Xu, Liang Lin, Wei-Shi Zheng, Xiaobai Liu
This paper aims at a newly raising task in visual surveillance: re-identifying people at a distance by matching body information, given several reference examples.