12 papers
DROSR: Degradation-Disentangled Representation for Real-World Omnidirectional Image Super-Resolution
Hongyu An, Xinfeng Zhang, Xu Fan +3
With the growing demand for immersive visual experiences, high-quality omnidirectional images (ODIs) have become increasingly important. However, limitations in imaging devices and…
OARS: Process-Aware Online Alignment for Generative Real-World Image Super-Resolution
Shijie Zhao, Xuanyu Zhang, Bin Chen +8
Aligning generative real-world image super-resolution models with human visual preference is challenging due to the perception--fidelity trade-off and diverse, unknown degradations…
Reasoning as Representation: Rethinking Visual Reinforcement Learning in Image Quality Assessment
Shijie Zhao, Xuanyu Zhang, Weiqi Li +4
Reasoning-based image quality assessment (IQA) models trained through reinforcement learning (RL) exhibit exceptional generalization, yet the underlying mechanisms and critical fac…
Improved Adversarial Diffusion Compression for Real-World Video Super-Resolution
Bin Chen, Weiqi Li, Shijie Zhao +4
While many diffusion models have achieved impressive results in real-world video super-resolution (Real-VSR) by generating rich and realistic details, their reliance on multi-step…
Generative Preprocessing for Image Compression with Pre-trained Diffusion Models
Mengxi Guo, Shijie Zhao, Junlin Li +1
Preprocessing is a well-established technique for optimizing compression, yet existing methods are predominantly Rate-Distortion (R-D) optimized and constrained by pixel-level fide…
Audio-Visual Cross-Modal Compression for Generative Face Video Coding
Youmin Xu, Mengxi Guo, Shijie Zhao +4
Generative face video coding (GFVC) is vital for modern applications like video conferencing, yet existing methods primarily focus on video motion while neglecting the significant…