13 citations · 26 across the 10 of their papers we have counts for
8 papers · 1 filter
A Renaissance of Explicit Motion Information Mining from Transformers for Action Recognition
Peiqin Zhuang, Lei Bai, Yichao Wu +4
Recently, action recognition has been dominated by transformer-based methods, thanks to their spatiotemporal contextual aggregation capacities. However, despite the significant pro…
Latent Distribution Adjusting for Face Anti-Spoofing
Qinghong Sun, Zhenfei Yin, Yichao Wu +2
With the development of deep learning, the field of face anti-spoofing (FAS) has witnessed great progress. FAS is usually considered a classification problem, where each class is a…
Towards Prompt-robust Face Privacy Protection via Adversarial Decoupling Augmentation Framework
Ruijia Wu, Yuhang Wang, Huafeng Shi +3
Denoising diffusion models have shown remarkable potential in various generation tasks. The open-source large-scale text-to-image model, Stable Diffusion, becomes prevalent as it c…
Universal Backdoor Attacks Detection via Adaptive Adversarial Probe
Yuhang Wang, Huafeng Shi, Rui Min +5
Extensive evidence has demonstrated that deep neural networks (DNNs) are vulnerable to backdoor attacks, which motivates the development of backdoor attacks detection. Most detecti…
DTG-SSOD: Dense Teacher Guidance for Semi-Supervised Object Detection
Gang Li, Xiang Li, Yujie Wang +3
The Mean-Teacher (MT) scheme is widely adopted in semi-supervised object detection (SSOD). In MT, the sparse pseudo labels, offered by the final predictions of the teacher (e.g., a…
Robust Face Anti-Spoofing with Dual Probabilistic Modeling
Yuanhan Zhang, Yichao Wu, Zhenfei Yin +2
The field of face anti-spoofing (FAS) has witnessed great progress with the surge of deep learning. Due to its data-driven nature, existing FAS methods are sensitive to the noise i…
CoupleFace: Relation Matters for Face Recognition Distillation
Jiaheng Liu, Haoyu Qin, Yichao Wu +3
Knowledge distillation is an effective method to improve the performance of a lightweight neural network (i.e., student model) by transferring the knowledge of a well-performed neu…
PseCo: Pseudo Labeling and Consistency Training for Semi-Supervised Object Detection
Gang Li, Xiang Li, Yujie Wang +3
In this paper, we delve into two key techniques in Semi-Supervised Object Detection (SSOD), namely pseudo labeling and consistency training. We observe that these two techniques cu…