activity
20222024
most citedEfficient Video Deblurring Guided by Motion Magnitude

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

KFD-NeRF: Rethinking Dynamic NeRF with Kalman Filter

Yifan Zhan, Zhuoxiao Li, Muyao Niu +4

We introduce KFD-NeRF, a novel dynamic neural radiance field integrated with an efficient and high-quality motion reconstruction framework based on Kalman filtering. Our key idea i…

cs.CV20241 cited

DiffBody: Human Body Restoration by Imagining with Generative Diffusion Prior

Yiming Zhang, Zhe Wang, Xinjie Li +5

Human body restoration plays a vital role in various applications related to the human body. Despite recent advances in general image restoration using generative models, their per…

cs.CV2023

Visibility Constrained Wide-band Illumination Spectrum Design for Seeing-in-the-Dark

Muyao Niu, Zhuoxiao Li, Zhihang Zhong +1

Seeing-in-the-dark is one of the most important and challenging computer vision tasks due to its wide applications and extreme complexities of in-the-wild scenarios. Existing arts…

cs.CV2022

Towards Real-World Video Deblurring by Exploring Blur Formation Process

Mingdeng Cao, Zhihang Zhong, Yanbo Fan +5

This paper aims at exploring how to synthesize close-to-real blurs that existing video deblurring models trained on them can generalize well to real-world blurry videos. In recent…

cs.CV20222 cited

Efficient Video Deblurring Guided by Motion Magnitude

Yusheng Wang, Yunfan Lu, Ye Gao +4

Video deblurring is a highly under-constrained problem due to the spatially and temporally varying blur. An intuitive approach for video deblurring includes two steps: a) detecting…

cs.CV2022

Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance

Zhihang Zhong, Xiao Sun, Zhirong Wu +3

We study the challenging problem of recovering detailed motion from a single motion-blurred image. Existing solutions to this problem estimate a single image sequence without consi…