8 papers
EchoStyle: Unlocking High-Fidelity Video Stylization with Reverse Data Synthesis
Huaqiu Li, Jiahao Wang, Sijia Cai +4
While image stylization has been studied extensively, video stylization remains a critical and largely unsolved challenge in the field of intelligent content creation. Existing met…
Self-supervised Dynamic Heterogeneous Degradation Modeling for Unified Zero-Shot Image Restoration
XiaoWan Hu, Jing Yang, HeNan Liu +2
Zero-shot image restoration provides a flexible way to handle diverse degradations without task-specific training. However, existing methods typically rely on stacked layers or pre…
Prompt-SID: Learning Structural Representation Prompt via Latent Diffusion for Single-Image Denoising
Huaqiu Li, Wang Zhang, Xiaowan Hu +3
Many studies have concentrated on constructing supervised models utilizing paired datasets for image denoising, which proves to be expensive and time-consuming. Current self-superv…
LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling
Huaqiu Li, Yong Wang, Tongwen Huang +3
Unified image restoration is a significantly challenging task in low-level vision. Existing methods either make tailored designs for specific tasks, limiting their generalizability…
Language-Guided and Motion-Aware Gait Representation for Generalizable Recognition
Zhengxian Wu, Chuanrui Zhang, Shenao Jiang +6
Gait recognition is emerging as a promising technology and an innovative field within computer vision, with a wide range of applications in remote human identification. However, ex…
Measuring and Controlling the Spectral Bias for Self-Supervised Image Denoising
Wang Zhang, Huaqiu Li, Xiaowan Hu +3
Current self-supervised denoising methods for paired noisy images typically involve mapping one noisy image through the network to the other noisy image. However, after measuring t…