44 citations · 103 across the 11 of their papers we have counts for
11 papers
Adversarial Attack and Defense in Deep Ranking
Mo Zhou, Le Wang, Zhenxing Niu +3
Deep Neural Network classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. However, the vulnerability of DNN-based…
ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization
Ziyi Liu, Le Wang, Qilin Zhang +4
The object of Weakly-supervised Temporal Action Localization (WS-TAL) is to localize all action instances in an untrimmed video with only video-level supervision. Due to the lack o…
Practical Relative Order Attack in Deep Ranking
Mo Zhou, Le Wang, Zhenxing Niu +4
Recent studies unveil the vulnerabilities of deep ranking models, where an imperceptible perturbation can trigger dramatic changes in the ranking result. While previous attempts fo…
Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization
Yuanhao Zhai, Le Wang, Wei Tang +3
Weakly-supervised Temporal Action Localization (W-TAL) aims to classify and localize all action instances in an untrimmed video under only video-level supervision. However, without…
Adversarial Ranking Attack and Defense
Mo Zhou, Zhenxing Niu, Le Wang +2
Deep Neural Network (DNN) classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. However, the vulnerability of DNN…
Ladder Loss for Coherent Visual-Semantic Embedding
Mo Zhou, Zhenxing Niu, Le Wang +3
For visual-semantic embedding, the existing methods normally treat the relevance between queries and candidates in a bipolar way -- relevant or irrelevant, and all "irrelevant" can…
Bimodal Stereo: Joint Shape and Pose Estimation from Color-Depth Image Pair
Chi Zhang, Yuehu Liu, Ying Wu +2
Mutual calibration between color and depth cameras is a challenging topic in multi-modal data registration. In this paper, we are confronted with a "Bimodal Stereo" problem, which…
Low-Latency Human Action Recognition with Weighted Multi-Region Convolutional Neural Network
Yunfeng Wang, Wengang Zhou, Qilin Zhang +2
Spatio-temporal contexts are crucial in understanding human actions in videos. Recent state-of-the-art Convolutional Neural Network (ConvNet) based action recognition systems frequ…
Visual Attribute-augmented Three-dimensional Convolutional Neural Network for Enhanced Human Action Recognition
Yunfeng Wang, Wengang Zhou, Qilin Zhang +1
Visual attributes in individual video frames, such as the presence of characteristic objects and scenes, offer substantial information for action recognition in videos. With indivi…
Attention-based Temporal Weighted Convolutional Neural Network for Action Recognition
Jinliang Zang, Le Wang, Ziyi Liu +4
Research in human action recognition has accelerated significantly since the introduction of powerful machine learning tools such as Convolutional Neural Networks (CNNs). However,…
Video-based Sign Language Recognition without Temporal Segmentation
Jie Huang, Wengang Zhou, Qilin Zhang +2
Millions of hearing impaired people around the world routinely use some variants of sign languages to communicate, thus the automatic translation of a sign language is meaningful a…