16 citations · 38 across the 9 of their papers we have counts for
9 papers
Adaptive Mixture of Low-Rank Experts for Robust Audio Spoofing Detection
Qixian Chen, Yuxiong Xu, Sara Mandelli +2
In audio spoofing detection, most studies rely on clean datasets, making models susceptible to real-world post-processing attacks, such as channel compression and noise. To overcom…
GM-DF: Generalized Multi-Scenario Deepfake Detection
Yingxin Lai, Zitong Yu, Jing Yang +3
Existing face forgery detection usually follows the paradigm of training models in a single domain, which leads to limited generalization capacity when unseen scenarios and unknown…
Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective
Xin Li, Bingchen Li, Xin Jin +2
In recent years, we have witnessed the great advancement of Deep neural networks (DNNs) in image restoration. However, a critical limitation is that they cannot generalize well to…
AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Xin Li +49
This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compress…
HST: Hierarchical Swin Transformer for Compressed Image Super-resolution
Bingchen Li, Xin Li, Yiting Lu +3
Compressed Image Super-resolution has achieved great attention in recent years, where images are degraded with compression artifacts and low-resolution artifacts. Since the complex…
Improving Cost Learning for JPEG Steganography by Exploiting JPEG Domain Knowledge
Weixuan Tang, Bin Li, Mauro Barni +2
Although significant progress in automatic learning of steganographic cost has been achieved recently, existing methods designed for spatial images are not well applicable to JPEG…