4 papers
IPAD-CLIP: Teaching CLIP to Detect Image Local Perceptual Artifacts
Juan Wang, Xinyu Sun, Ke Zhang +4
Current image quality assessment methods are heavily biased towards global distortions (e.g., noise, blur), neglecting local perceptual artifacts such as ghosting, lens flare, and…
Efficient Event-Based Semantic Segmentation via Exploiting Frame-Event Fusion: A Hybrid Neural Network Approach
Hebei Li, Yansong Peng, Jiahui Yuan +4
Event cameras have recently been introduced into image semantic segmentation, owing to their high temporal resolution and other advantageous properties. However, existing event-bas…
Event-Enhanced Blurry Video Super-Resolution
Dachun Kai, Yueyi Zhang, Jin Wang +3
In this paper, we tackle the task of blurry video super-resolution (BVSR), aiming to generate high-resolution (HR) videos from low-resolution (LR) and blurry inputs. Current BVSR m…
Event-assisted Low-Light Video Object Segmentation
Hebei Li, Jin Wang, Jiahui Yuan +6
In the realm of video object segmentation (VOS), the challenge of operating under low-light conditions persists, resulting in notably degraded image quality and compromised accurac…