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A fast and effective motion deblurring method has great application values in real life. This work presents an innovative approach in which a self-paced learning is combined with GAN to deblur image. First, We explain that a proper…

Computer Vision and Pattern Recognition · Computer Science 2019-02-26 Yiwei Zhang , Chunbiao Zhu , Ge Li , Yuan Zhao , Haifeng Shen

Image based modeling and laser scanning are two commonly used approaches in large-scale architectural scene reconstruction nowadays. In order to generate a complete scene reconstruction, an effective way is to completely cover the scene…

Computer Vision and Pattern Recognition · Computer Science 2019-09-19 Xiang Gao , Shuhan Shen , Lingjie Zhu , Tianxin Shi , Zhiheng Wang , Zhanyi Hu

Moving objects are frequently seen in daily life and usually appear blurred in images due to their motion. While general object retrieval is a widely explored area in computer vision, it primarily focuses on sharp and static objects, and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Rong Zou , Marc Pollefeys , Denys Rozumnyi

We investigate the problem of estimating the 3D shape of an object defined by a set of 3D landmarks, given their 2D correspondences in a single image. A successful approach to alleviating the reconstruction ambiguity is the 3D deformable…

Computer Vision and Pattern Recognition · Computer Science 2017-01-12 Xiaowei Zhou , Menglong Zhu , Spyridon Leonardos , Kostas Daniilidis

How can one efficiently generate high-quality, wide-scope 3D scenes from arbitrary single images? Existing methods suffer several drawbacks, such as requiring multi-view data, time-consuming per-scene optimization, distorted geometry in…

Computer Vision and Pattern Recognition · Computer Science 2025-04-29 Hanwen Liang , Junli Cao , Vidit Goel , Guocheng Qian , Sergei Korolev , Demetri Terzopoulos , Konstantinos N. Plataniotis , Sergey Tulyakov , Jian Ren

We seek to answer the question: what can a motion-blurred image reveal about a scene's past, present, and future? Although motion blur obscures image details and degrades visual quality, it also encodes information about scene and camera…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 SaiKiran Tedla , Kelly Zhu , Trevor Canham , Felix Taubner , Michael S. Brown , Kiriakos N. Kutulakos , David B. Lindell

We introduce a novel learning-based method to reconstruct the high-quality geometry and complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images captured by wide-baseline cameras under collocated point…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Sai Bi , Zexiang Xu , Kalyan Sunkavalli , David Kriegman , Ravi Ramamoorthi

Turbulence-degraded image frames are distorted by both turbulent deformations and space-time-varying blurs. To suppress these effects, we propose a multi-frame reconstruction scheme to recover a latent image from the observed image…

Computer Vision and Pattern Recognition · Computer Science 2017-12-12 Chun Pong Lau , Yu Hin Lai , Lok Ming Lui

Neural 3D scene reconstruction methods have achieved impressive performance when reconstructing complex geometry and low-textured regions in indoor scenes. However, these methods heavily rely on 3D data which is costly and time-consuming to…

Computer Vision and Pattern Recognition · Computer Science 2023-07-06 Yi Guo , Che Sun , Yunde Jia , Yuwei Wu

Demystifying complex human-ground interactions is essential for accurate and realistic 3D human motion reconstruction from RGB videos, as it ensures consistency between the humans and the ground plane. Prior methods have modeled…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Sihan Ma , Qiong Cao , Hongwei Yi , Jing Zhang , Dacheng Tao

Gaussian splatting typically requires dense observations of the scene and can fail to reconstruct occluded and unobserved areas. We propose a latent diffusion model to reconstruct a complete 3D scene with Gaussian splats, including the…

Computer Vision and Pattern Recognition · Computer Science 2025-09-01 Ziwei Liao , Mohamed Sayed , Steven L. Waslander , Sara Vicente , Daniyar Turmukhambetov , Michael Firman

Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process. For event-based cameras, however, fast motion can be captured as events at high time…

Computer Vision and Pattern Recognition · Computer Science 2020-04-14 Zhe Jiang , Yu Zhang , Dongqing Zou , Jimmy Ren , Jiancheng Lv , Yebin Liu

With the boost in the number of spacecraft launches in the current decades, the space debris problem is daily becoming significantly crucial. For sustainable space utilization, the continuous removal of space debris is the most severe…

Robotics · Computer Science 2024-08-05 Kentaro Uno , Takehiro Matsuoka , Akiyoshi Uchida , Kazuya Yoshida

Dynamic scene deblurring is a challenging problem in computer vision. It is difficult to accurately estimate the spatially varying blur kernel by traditional methods. Data-driven-based methods usually employ kernel-free end-to-end mapping…

Image and Video Processing · Electrical Eng. & Systems 2020-08-20 Xiaoguang Li , Feifan Yang , Kin Man Lam , Li Zhuo , Jiafeng Li

Recovering surface albedos from photogrammetric images for realistic rendering and synthetic environments can greatly facilitate its downstream applications in VR/AR/MR and digital twins. The textured 3D models from standard photogrammetric…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Shuang Song , Rongjun Qin

High-quality scene reconstruction and novel view synthesis based on Gaussian Splatting (3DGS) typically require steady, high-quality photographs, often impractical to capture with handheld cameras. We present a method that adapts to camera…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Otto Seiskari , Jerry Ylilammi , Valtteri Kaatrasalo , Pekka Rantalankila , Matias Turkulainen , Juho Kannala , Esa Rahtu , Arno Solin

We propose a new technique for estimating spatially varying parametric materials from a single image of an object with unknown shape in unknown illumination. Our method uses a low-order parametric reflectance model, and incorporates strong…

Graphics · Computer Science 2019-12-30 Kevin Karsch , David Forsyth

Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Danpeng Chen , Hai Li , Weicai Ye , Yifan Wang , Weijian Xie , Shangjin Zhai , Nan Wang , Haomin Liu , Hujun Bao , Guofeng Zhang

We focus on the task of estimating a physically plausible articulated human motion from monocular video. Existing approaches that do not consider physics often produce temporally inconsistent output with motion artifacts, while…

Computer Vision and Pattern Recognition · Computer Science 2022-05-26 Erik Gärtner , Mykhaylo Andriluka , Hongyi Xu , Cristian Sminchisescu

Blind motion deblurring involves reconstructing a sharp image from an observation that is blurry. It is a problem that is ill-posed and lies in the categories of image restoration problems. The training data-based methods for image…

Computer Vision and Pattern Recognition · Computer Science 2020-11-10 Harshil Jain , Rohit Patil , Indra Deep Mastan , Shanmuganathan Raman