collaborators

19 papers

cs.CV2026

Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding

Zihan Zhou, Libo Zhu, Jue Gong +4

Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured image readability with color…

cs.CV2026

Q-DiT4SR: Exploration of Detail-Preserving Diffusion Transformer Quantization for Real-World Image Super-Resolution

Xun Zhang, Kaicheng Yang, Hongliang Lu +3

Recently, Diffusion Transformers (DiTs) have emerged in Real-World Image Super-Resolution (Real-ISR) to generate high-quality textures, yet their heavy inference burden hinders rea…

cs.CV2026

DiffST: Spatiotemporal-Aware Diffusion for Real-World Space-Time Video Super-Resolution

Zheng Chen, Ruofan Yang, Jin Han +5

Diffusion-based models have shown strong performance in video super-resolution (VSR) and video frame interpolation (VFI). However, their role in the coupled space-time video super-…

cs.CV2026

Towards Redundancy Reduction in Diffusion Models for Efficient Video Super-Resolution

Jinpei Guo, Yifei Ji, Shengwei Wang +8

Diffusion models have recently shown promising results for video super-resolution (VSR). However, directly adapting generative diffusion models to VSR can result in redundancy, sin…

cs.CV2026

QuantVSR: Low-Bit Post-Training Quantization for Real-World Video Super-Resolution

Bowen Chai, Zheng Chen, Libo Zhu +3

Diffusion models have shown superior performance in real-world video super-resolution (VSR). However, the slow processing speeds and heavy resource consumption of diffusion models…

cs.CV2026

LSGQuant: Layer-Sensitivity Guided Quantization for One-Step Diffusion Real-World Video Super-Resolution

Tianxing Wu, Zheng Chen, Cirou Xu +5

One-Step Diffusion Models have demonstrated promising capability and fast inference in video super-resolution (VSR) for real-world. Nevertheless, the substantial model size and hig…