232 citations · 264 across the 16 of their papers we have counts for
16 papers
Hierarchical Semantic Perceptual Listener Head Video Generation: A High-performance Pipeline
Zhigang Chang, Weitai Hu, Qing Yang +1
In dyadic speaker-listener interactions, the listener's head reactions along with the speaker's head movements, constitute an important non-verbal semantic expression together. The…
Understanding the Robustness of 3D Object Detection with Bird's-Eye-View Representations in Autonomous Driving
Zijian Zhu, Yichi Zhang, Hai Chen +5
3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the…
To Make Yourself Invisible with Adversarial Semantic Contours
Yichi Zhang, Zijian Zhu, Hang Su +4
Modern object detectors are vulnerable to adversarial examples, which may bring risks to real-world applications. The sparse attack is an important task which, compared with the po…
A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking
Chang Liu, Yinpeng Dong, Wenzhao Xiang +7
The robustness of deep neural networks is usually lacking under adversarial examples, common corruptions, and distribution shifts, which becomes an important research problem in th…
Improving Model Generalization by On-manifold Adversarial Augmentation in the Frequency Domain
Chang Liu, Wenzhao Xiang, Yuan He +3
Deep neural networks (DNNs) may suffer from significantly degenerated performance when the training and test data are of different underlying distributions. Despite the importance…
Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification
Zhigang Chang, Zhao Yang, Yongbiao Chen +2
ideo-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods f…
Subtask-dominated Transfer Learning for Long-tail Person Search
Chuang Liu, Hua Yang, Qin Zhou +1
Person search unifies person detection and person re-identification (Re-ID) to locate query persons from the panoramic gallery images. One major challenge comes from the imbalanced…
You Cannot Easily Catch Me: A Low-Detectable Adversarial Patch for Object Detectors
Zijian Zhu, Hang Su, Chang Liu +2
Blind spots or outright deceit can bedevil and deceive machine learning models. Unidentified objects such as digital "stickers," also known as adversarial patches, can fool facial…
Improving the Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator
Wenzhao Xiang, Hang Su, Chang Liu +2
As designers of artificial intelligence try to outwit hackers, both sides continue to hone in on AI's inherent vulnerabilities. Designed and trained from certain statistical distri…
Improving Visual Quality of Unrestricted Adversarial Examples with Wavelet-VAE
Wenzhao Xiang, Chang Liu, Shibao Zheng
Traditional adversarial examples are typically generated by adding perturbation noise to the input image within a small matrix norm. In practice, un-restricted adversarial attack h…
Making Person Search Enjoy the Merits of Person Re-identification
Chuang Liu, Hua Yang, Qin Zhou +1
Person search is an extended task of person re-identification (Re-ID). However, most existing one-step person search works have not studied how to employ existing advanced Re-ID mo…
Distribution Context Aware Loss for Person Re-identification
Zhigang Chang, Qin Zhou, Mingyang Yu +3
To learn the optimal similarity function between probe and gallery images in Person re-identification, effective deep metric learning methods have been extensively explored to obta…
Learning to Self-Train for Semi-Supervised Few-Shot Classification
Xinzhe Li, Qianru Sun, Yaoyao Liu +4
Few-shot classification (FSC) is challenging due to the scarcity of labeled training data (e.g. only one labeled data point per class). Meta-learning has shown to achieve promising…
Robust and Efficient Graph Correspondence Transfer for Person Re-identification
Qin Zhou, Heng Fan, Hua Yang +4
Spatial misalignment caused by variations in poses and viewpoints is one of the most critical issues that hinders the performance improvement in existing person re-identification (…
Graph Correspondence Transfer for Person Re-identification
Qin Zhou, Heng Fan, Shibao Zheng +4
In this paper, we propose a graph correspondence transfer (GCT) approach for person re-identification. Unlike existing methods, the GCT model formulates person re-identification as…
Weighted Bilinear Coding over Salient Body Parts for Person Re-identification
Zhigang Chang, Qin Zhou, Heng Fan +4
Deep convolutional neural networks (CNNs) have demonstrated dominant performance in person re-identification (Re-ID). Existing CNN based methods utilize global average pooling (GAP…