Search Results for author: Tianzhu Zhang

Found 28 papers, 6 papers with code

Cross-Modality Transformer for Visible-Infrared Person Re-Identification

no code implementations ECCV 2022 Kongzhu Jiang, Tianzhu Zhang, Xiang Liu, Bingqiao Qian, Yongdong Zhang, Feng Wu ;

To alleviate the above issues, we propose a novel Cross-Modality Transformer (CMT) to jointly explore a modality-level alignment module and an instance-level module for VI-ReID.

Person Re-Identification

A Keypoint-based Global Association Network for Lane Detection

1 code implementation CVPR 2022 Jinsheng Wang, Yinchao Ma, Shaofei Huang, Tianrui Hui, Fei Wang, Chen Qian, Tianzhu Zhang

Earlier works follow a top-down roadmap to regress predefined anchors into various shapes of lane lines, which lacks enough flexibility to fit complex shapes of lanes due to the fixed anchor shapes.

Ranked #3 on Lane Detection on TuSimple (F1 score metric)

Association Keypoint Estimation +1

Motion-Modulated Temporal Fragment Alignment Network for Few-Shot Action Recognition

no code implementations CVPR 2022 Jiamin Wu, Tianzhu Zhang, Zhe Zhang, Feng Wu, Yongdong Zhang

To address this issue, we propose an end-to-end Motion-modulated Temporal Fragment Alignment Network (MTFAN) by jointly exploring the task-specific motion modulation and the multi-level temporal fragment alignment for Few-Shot Action Recognition (FSAR).

Few-Shot action recognition Few Shot Action Recognition +1

Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking

no code implementations23 Nov 2021 Pengfei Zhu, Hongtao Yu, Kaihua Zhang, Yu Wang, Shuai Zhao, Lei Wang, Tianzhu Zhang, QinGhua Hu

To address this issue, segmentation-based trackers have been proposed that employ per-pixel matching to improve the tracking performance of deformable objects effectively.

Visual Object Tracking Visual Tracking

Geometry Uncertainty Projection Network for Monocular 3D Object Detection

1 code implementation ICCV 2021 Yan Lu, Xinzhu Ma, Lei Yang, Tianzhu Zhang, Yating Liu, Qi Chu, Junjie Yan, Wanli Ouyang

In this paper, we propose a Geometry Uncertainty Projection Network (GUP Net) to tackle the error amplification problem at both inference and training stages.

Depth Estimation Monocular 3D Object Detection +1

Lesion-Aware Transformers for Diabetic Retinopathy Grading

no code implementations CVPR 2021 Rui Sun, Yihao Li, Tianzhu Zhang, Zhendong Mao, Feng Wu, Yongdong Zhang

First, to the best of our knowledge, this is the first work to formulate lesion discovery as a weakly supervised lesion localization problem via a transformer decoder.

Diabetic Retinopathy Grading

Uncertainty Guided Collaborative Training for Weakly Supervised Temporal Action Detection

no code implementations CVPR 2021 Wenfei Yang, Tianzhu Zhang, Xiaoyuan Yu, Tian Qi, Yongdong Zhang, Feng Wu

To alleviate this problem, we propose a novel Uncertainty Guided Collaborative Training (UGCT) strategy, which mainly includes two key designs: (1) The first design is an online pseudo label generation module, in which the RGB and FLOW streams work collaboratively to learn from each other.

Action Detection Pseudo Label

Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer

no code implementations CVPR 2021 Yulin Li, Jianfeng He, Tianzhu Zhang, Xiang Liu, Yongdong Zhang, Feng Wu

To address these issues, we propose a novel end-to-end Part-Aware Transformer (PAT) for occluded person Re-ID through diverse part discovery via a transformer encoderdecoder architecture, including a pixel context based transformer encoder and a part prototype based transformer decoder.

Person Re-Identification

Action Unit Memory Network for Weakly Supervised Temporal Action Localization

no code implementations CVPR 2021 Wang Luo, Tianzhu Zhang, Wenfei Yang, Jingen Liu, Tao Mei, Feng Wu, Yongdong Zhang

In this paper, we present an Action Unit Memory Network (AUMN) for weakly supervised temporal action localization, which can mitigate the above two challenges by learning an action unit memory bank.

Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1

Foreground Activation Maps for Weakly Supervised Object Localization

no code implementations ICCV 2021 Meng Meng, Tianzhu Zhang, Qi Tian, Yongdong Zhang, Feng Wu

To the best of our knowledge, this is the first work that can achieve remarkable performance for both tasks by optimizing them jointly via FAM for WSOL.

Classification Weakly-Supervised Object Localization

Meta-Attack: Class-Agnostic and Model-Agnostic Physical Adversarial Attack

no code implementations ICCV 2021 Weiwei Feng, Baoyuan Wu, Tianzhu Zhang, Yong Zhang, Yongdong Zhang

To tackle these issues, we propose a class-agnostic and model-agnostic physical adversarial attack model (Meta-Attack), which is able to not only generate robust physical adversarial examples by simulating color and shape distortions, but also generalize to attacking novel images and novel DNN models by accessing a few digital and physical images.

Adversarial Attack Few-Shot Learning

Task-Aware Part Mining Network for Few-Shot Learning

no code implementations ICCV 2021 Jiamin Wu, Tianzhu Zhang, Yongdong Zhang, Feng Wu

The task-aware part filters can adapt to any individual task and automatically mine task-related local parts even for an unseen task.

Few-Shot Learning

Graph Structured Network for Image-Text Matching

1 code implementation CVPR 2020 Chunxiao Liu, Zhendong Mao, Tianzhu Zhang, Hongtao Xie, Bin Wang, Yongdong Zhang

The GSMN explicitly models object, relation and attribute as a structured phrase, which not only allows to learn correspondence of object, relation and attribute separately, but also benefits to learn fine-grained correspondence of structured phrase.

Cross-Modal Retrieval Text Matching

Cross-modality Person re-identification with Shared-Specific Feature Transfer

no code implementations CVPR 2020 Yan Lu, Yue Wu, Bin Liu, Tianzhu Zhang, Baopu Li, Qi Chu, Nenghai Yu

In this paper, we tackle the above limitation by proposing a novel cross-modality shared-specific feature transfer algorithm (termed cm-SSFT) to explore the potential of both the modality-shared information and the modality-specific characteristics to boost the re-identification performance.

Cross-Modality Person Re-identification Person Re-Identification

Describe and Attend to Track: Learning Natural Language guided Structural Representation and Visual Attention for Object Tracking

no code implementations25 Nov 2018 Xiao Wang, Chenglong Li, Rui Yang, Tianzhu Zhang, Jin Tang, Bin Luo

To refine the states of the target and re-track the target when it is back to view from heavy occlusion and out of view, we elaborately design a novel subnetwork to learn the target-driven visual attentions from the guidance of both visual and natural language cues.

Object Tracking

Joint Pose and Expression Modeling for Facial Expression Recognition

no code implementations CVPR 2018 Feifei Zhang, Tianzhu Zhang, Qirong Mao, Changsheng Xu

First, the encoder-decoder structure of the generator can learn a generative and discriminative identity representation for face images.

Facial Expression Recognition (FER) Image Generation

3D Part-Based Sparse Tracker With Automatic Synchronization and Registration

no code implementations CVPR 2016 Adel Bibi, Tianzhu Zhang, Bernard Ghanem

In this paper, we present a part-based sparse tracker in a particle filter framework where both the motion and appearance model are formulated in 3D.

Occlusion Handling

Structural Correlation Filter for Robust Visual Tracking

no code implementations CVPR 2016 Si Liu, Tianzhu Zhang, Xiaochun Cao, Changsheng Xu

In this paper, we propose a novel structural correlation filter (SCF) model for robust visual tracking.

Visual Tracking

In Defense of Sparse Tracking: Circulant Sparse Tracker

no code implementations CVPR 2016 Tianzhu Zhang, Adel Bibi, Bernard Ghanem

Sparse representation has been introduced to visual tracking by finding the best target candidate with minimal reconstruction error within the particle filter framework.

Visual Tracking

Structural Sparse Tracking

no code implementations CVPR 2015 Tianzhu Zhang, Si Liu, Changsheng Xu, Shuicheng Yan, Bernard Ghanem, Narendra Ahuja, Ming-Hsuan Yang

Sparse representation has been applied to visual tracking by finding the best target candidate with minimal reconstruction error by use of target templates.

Visual Tracking

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