most citedWeakly Supervised Temporal Action Localization with Segment-Level Labels

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

GazeForensics: DeepFake Detection via Gaze-guided Spatial Inconsistency Learning

Qinlin He, Chunlei Peng, Decheng Liu +2

DeepFake detection is pivotal in personal privacy and public safety. With the iterative advancement of DeepFake techniques, high-quality forged videos and images are becoming incre…

cs.CV2023

Enhancing Robust Representation in Adversarial Training: Alignment and Exclusion Criteria

Nuoyan Zhou, Nannan Wang, Decheng Liu +2

Deep neural networks are vulnerable to adversarial noise. Adversarial Training (AT) has been demonstrated to be the most effective defense strategy to protect neural networks from…

cs.CV20203 cited

Weakly Supervised Temporal Action Localization with Segment-Level Labels

Xinpeng Ding, Nannan Wang, Xinbo Gao +3

Temporal action localization presents a trade-off between test performance and annotation-time cost. Fully supervised methods achieve good performance with time-consuming boundary…

cs.CV20201 cited

Facial Attribute Capsules for Noise Face Super Resolution

Jingwei Xin, Nannan Wang, Xinrui Jiang +3

Existing face super-resolution (SR) methods mainly assume the input image to be noise-free. Their performance degrades drastically when applied to real-world scenarios where the in…

cs.CV20201 cited

Video Face Super-Resolution with Motion-Adaptive Feedback Cell

Jingwei Xin, Nannan Wang, Jie Li +2

Video super-resolution (VSR) methods have recently achieved a remarkable success due to the development of deep convolutional neural networks (CNN). Current state-of-the-art CNN me…