4 citations · 9 across the 12 of their papers we have counts for
13 papers
Toward Robust and 3D-Aware RGB-NIR Imaging in the Dark
Muyao Niu, Mingze Ma, Yifan Zhan +5
Robust low-light imaging remains challenging for the community. Recent studies have explored fusing Near-Infrared (NIR) with noisy RGB to achieve improved enhancement, yet most met…
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…
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…
Fooling Polarization-based Vision using Locally Controllable Polarizing Projection
Zhuoxiao Li, Zhihang Zhong, Shohei Nobuhara +2
Polarization is a fundamental property of light that encodes abundant information regarding surface shape, material, illumination and viewing geometry. The computer vision communit…
ClipCrop: Conditioned Cropping Driven by Vision-Language Model
Zhihang Zhong, Mingxi Cheng, Zhirong Wu +7
Image cropping has progressed tremendously under the data-driven paradigm. However, current approaches do not account for the intentions of the user, which is an issue especially w…
Blur Interpolation Transformer for Real-World Motion from Blur
Zhihang Zhong, Mingdeng Cao, Xiang Ji +2
This paper studies the challenging problem of recovering motion from blur, also known as joint deblurring and interpolation or blur temporal super-resolution. The challenges are tw…
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…
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…
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…
Learning Adaptive Warping for Real-World Rolling Shutter Correction
Mingdeng Cao, Zhihang Zhong, Jiahao Wang +2
This paper proposes the first real-world rolling shutter (RS) correction dataset, BS-RSC, and a corresponding model to correct the RS frames in a distorted video. Mobile devices in…
Bringing Rolling Shutter Images Alive with Dual Reversed Distortion
Zhihang Zhong, Mingdeng Cao, Xiao Sun +5
Rolling shutter (RS) distortion can be interpreted as the result of picking a row of pixels from instant global shutter (GS) frames over time during the exposure of the RS camera.…
Real-world Video Deblurring: A Benchmark Dataset and An Efficient Recurrent Neural Network
Zhihang Zhong, Ye Gao, Yinqiang Zheng +2
Real-world video deblurring in real time still remains a challenging task due to the complexity of spatially and temporally varying blur itself and the requirement of low computati…
Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes
Zhihang Zhong, Yinqiang Zheng, Imari Sato
Joint rolling shutter correction and deblurring (RSCD) techniques are critical for the prevalent CMOS cameras. However, current approaches are still based on conventional energy op…