1 citations · 3 across the 6 of their papers we have counts for
6 papers
Self-Cooperation Knowledge Distillation for Novel Class Discovery
Yuzheng Wang, Zhaoyu Chen, Dingkang Yang +2
Novel Class Discovery (NCD) aims to discover unknown and novel classes in an unlabeled set by leveraging knowledge already learned about known classes. Existing works focus on inst…
De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts
Yuzheng Wang, Dingkang Yang, Zhaoyu Chen +5
Data-Free Knowledge Distillation (DFKD) is a promising task to train high-performance small models to enhance actual deployment without relying on the original training data. Exist…
Learning Causality-inspired Representation Consistency for Video Anomaly Detection
Yang Liu, Zhaoyang Xia, Mengyang Zhao +7
Video anomaly detection is an essential yet challenging task in the multimedia community, with promising applications in smart cities and secure communities. Existing methods attem…
AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception
Dingkang Yang, Shuai Huang, Zhi Xu +12
Driver distraction has become a significant cause of severe traffic accidents over the past decade. Despite the growing development of vision-driven driver monitoring systems, the…
Explicit and Implicit Knowledge Distillation via Unlabeled Data
Yuzheng Wang, Zuhao Ge, Zhaoyu Chen +4
Data-free knowledge distillation is a challenging model lightweight task for scenarios in which the original dataset is not available. Previous methods require a lot of extra compu…
Adversarial Contrastive Distillation with Adaptive Denoising
Yuzheng Wang, Zhaoyu Chen, Dingkang Yang +4
Adversarial Robustness Distillation (ARD) is a novel method to boost the robustness of small models. Unlike general adversarial training, its robust knowledge transfer can be less…