9 citations · 18 across the 9 of their papers we have counts for
10 papers
LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
Yutong Xiao, Ran Ran, Jiwei Wei +4
The rapid advancement of generative technologies has made synthetic images nearly indistinguishable from real ones, thereby creating an urgent need for robust detectors to counter…
UVEB: A Large-scale Benchmark and Baseline Towards Real-World Underwater Video Enhancement
Yaofeng Xie, Lingwei Kong, Kai Chen +4
Learning-based underwater image enhancement (UIE) methods have made great progress. However, the lack of large-scale and high-quality paired training samples has become the main bo…
Medium Transmission Map Matters for Learning to Restore Real-World Underwater Images
Yan Kai, Liang Lanyue, Zheng Ziqiang +2
Underwater visual perception is essentially important for underwater exploration, archeology, ecosystem and so on. The low illumination, light reflections, scattering, absorption a…
ReMOTS: Self-Supervised Refining Multi-Object Tracking and Segmentation
Fan Yang, Xin Chang, Chenyu Dang +4
We aim to improve the performance of Multiple Object Tracking and Segmentation (MOTS) by refinement. However, it remains challenging for refining MOTS results, which could be attri…
EncryptGAN: Image Steganography with Domain Transform
Ziqiang Zheng, Hongzhi Liu, Zhibin Yu +4
We propose an image steganographic algorithm called EncryptGAN, which disguises private image communication in an open communication channel. The insight is that content transform…
ReshapeGAN: Object Reshaping by Providing A Single Reference Image
Ziqiang Zheng, Yang Wu, Zhibin Yu +3
The aim of this work is learning to reshape the object in an input image to an arbitrary new shape, by just simply providing a single reference image with an object instance in the…