5 papers · 2 filters
Accelerating Video Diffusion Models via Distribution Matching
Yuanzhi Zhu, Hanshu Yan, Huan Yang +2
Generative models, particularly diffusion models, have made significant success in data synthesis across various modalities, including images, videos, and 3D assets. However, curre…
OFTSR: One-Step Flow for Image Super-Resolution with Tunable Fidelity-Realism Trade-offs
Yuanzhi Zhu, Ruiqing Wang, Shilin Lu +3
Recent advances in diffusion and flow-based generative models have demonstrated remarkable success in image restoration tasks, achieving superior perceptual quality compared to tra…
Teaching Tailored to Talent: Adverse Weather Restoration via Prompt Pool and Depth-Anything Constraint
Sixiang Chen, Tian Ye, Kai Zhang +3
Recent advancements in adverse weather restoration have shown potential, yet the unpredictable and varied combinations of weather degradations in the real world pose significant ch…
Task-Aware Dynamic Transformer for Efficient Arbitrary-Scale Image Super-Resolution
Tianyi Xu, Yiji Zhou, Xiaotao Hu +4
Arbitrary-scale super-resolution (ASSR) aims to learn a single model for image super-resolution at arbitrary magnifying scales. Existing ASSR networks typically comprise an off-the…
From Darkness to Detail: Frequency-Aware SSMs for Low-Light Vision
Eashan Adhikarla, Kai Zhang, Gong Chen +2
Low-light image enhancement remains a persistent challenge in computer vision, where state-of-the-art models are often hampered by hardware constraints and computational inefficien…