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Image sequences filtering have recently become a very important technical problem especially with the advent of new technology in multimedia and video systems applications. Often image sequences are corrupted by some amount of noise…

Computer Vision and Pattern Recognition · Computer Science 2013-04-18 Soumaya Hichri , Faouzi Benzarti , Hamid Amiri

The precise reconstruction of 3D objects from a single RGB image in complex scenes presents a critical challenge in virtual reality, autonomous driving, and robotics. Existing neural implicit 3D representation methods face significant…

Computer Vision and Pattern Recognition · Computer Science 2024-11-21 Luoxi Zhang , Pragyan Shrestha , Yu Zhou , Chun Xie , Itaru Kitahara

Deblurring can not only provide visually more pleasant pictures and make photography more convenient, but also can improve the performance of objection detection as well as tracking. However, removing dynamic scene blur from images is a…

Computer Vision and Pattern Recognition · Computer Science 2023-01-19 Jiawei Zhang , Jinshan Pan , Daoye Wang , Shangchen Zhou , Xing Wei , Furong Zhao , Jianbo Liu , Jimmy Ren

Optical coherence tomography (OCT) is an important interferometric diagnostic technique which provides cross-sectional views of the subsurface microstructure of biological tissues. However, the imaging quality of high-speed OCT is limited…

Computer Vision and Pattern Recognition · Computer Science 2015-03-13 Liheng Bian , Jinli Suo , Feng Chen , Qionghai Dai

Empowering 3D Gaussian Splatting with generalization ability is appealing. However, existing generalizable 3D Gaussian Splatting methods are largely confined to narrow-range interpolation between stereo images due to their heavy backbones,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yunsong Wang , Tianxin Huang , Hanlin Chen , Gim Hee Lee

Self-supervised video denoising aims to remove noise from videos without relying on ground truth data, leveraging the video itself to recover clean frames. Existing methods often rely on simplistic feature stacking or apply optical flow…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Zikang Chen , Tao Jiang , Xiaowan Hu , Wang Zhang , Huaqiu Li , Haoqian Wang

We propose a new approach called LiDAR-Flow to robustly estimate a dense scene flow by fusing a sparse LiDAR with stereo images. We take the advantage of the high accuracy of LiDAR to resolve the lack of information in some regions of…

Computer Vision and Pattern Recognition · Computer Science 2019-12-16 Ramy Battrawy , René Schuster , Oliver Wasenmüller , Qing Rao , Didier Stricker

Noise reduction is one the most important and still active research topic in low-level image processing due to its high impact on object detection and scene understanding for computer vision systems. Recently, we can observe a substantial…

Computer Vision and Pattern Recognition · Computer Science 2020-05-22 Krystian Radlak , Lukasz Malinski , Bogdan Smolka

Light field cameras have been proved to be powerful tools for 3D reconstruction and virtual reality applications. However, the limited resolution of light field images brings a lot of difficulties for further information display and…

Image and Video Processing · Electrical Eng. & Systems 2020-08-27 Qingyan Sun , Shuo Zhang , Song Chang , Lixi Zhu , Youfang Lin

Active stereo technique using single pattern projection, a.k.a. one-shot 3D scan, have drawn a wide attention from industry, medical purposes, etc. One severe drawback of one-shot 3D scan is sparse reconstruction. In addition, since spatial…

Computer Vision and Pattern Recognition · Computer Science 2023-09-27 Hiroto Harada , Michihiro Mikamo , Ryo Furukawa , Ryushuke Sagawa , Hiroshi Kawasaki

We introduce a simple yet effective approach for separating transmitted and reflected light. Our key insight is that the powerful novel view synthesis capabilities provided by modern inverse rendering methods (e.g.,~3D Gaussian splatting)…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Mingyang Xie , Haoming Cai , Sachin Shah , Yiran Xu , Brandon Y. Feng , Jia-Bin Huang , Christopher A. Metzler

Novel view synthesis of dynamic scenes has been an intriguing yet challenging problem. Despite recent advancements, simultaneously achieving high-resolution photorealistic results, real-time rendering, and compact storage remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Zhan Li , Zhang Chen , Zhong Li , Yi Xu

Airborne laser scanning and photogrammetry are two main techniques to obtain 3D data representing the object surface. Due to the high cost of laser scanning, we want to explore the potential of using point clouds derived by dense image…

Computer Vision and Pattern Recognition · Computer Science 2018-07-26 Zhenchao Zhang , Markus Gerke , George Vosselman , Michael Ying Yang

We propose MFT -- Multi-Flow dense Tracker -- a novel method for dense, pixel-level, long-term tracking. The approach exploits optical flows estimated not only between consecutive frames, but also for pairs of frames at logarithmically…

Computer Vision and Pattern Recognition · Computer Science 2023-11-13 Michal Neoral , Jonáš Šerých , Jiří Matas

3D Gaussian splatting enables high-quality novel view synthesis (NVS) at real-time frame rates. However, its quality drops sharply as we depart from the training views. Thus, dense captures are needed to match the high-quality expectations…

Computer Vision and Pattern Recognition · Computer Science 2025-08-06 Tobias Fischer , Samuel Rota Bulò , Yung-Hsu Yang , Nikhil Keetha , Lorenzo Porzi , Norman Müller , Katja Schwarz , Jonathon Luiten , Marc Pollefeys , Peter Kontschieder

3D object detection from monocular image(s) is a challenging and long-standing problem of computer vision. To combine information from different perspectives without troublesome 2D instance tracking, recent methods tend to aggregate…

Computer Vision and Pattern Recognition · Computer Science 2022-09-01 Jianlin Liu , Zhuofei Huang , Dihe Huang , Shang Xu , Ying Chen , Yong Liu

Recently, 3D convolutional networks yield good performance in action recognition. However, optical flow stream is still needed to ensure better performance, the cost of which is very high. In this paper, we propose a fast but effective way…

Computer Vision and Pattern Recognition · Computer Science 2020-01-17 Li Tao , Xueting Wang , Toshihiko Yamasaki

Reconstructing 3D scenes and synthesizing novel views has seen rapid progress in recent years. Neural Radiance Fields demonstrated that continuous volumetric radiance fields can achieve high-quality image synthesis, but their long training…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Jan Held , Renaud Vandeghen , Sanghyun Son , Daniel Rebain , Matheus Gadelha , Yi Zhou , Ming C. Lin , Marc Van Droogenbroeck , Andrea Tagliasacchi

We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view captures. Our approach begins with scene partitioning for…

Computer Vision and Pattern Recognition · Computer Science 2025-08-01 Zhensheng Yuan , Haozhi Huang , Zhen Xiong , Di Wang , Guanghua Yang

Each photo in an image burst can be considered a sample of a complex 3D scene: the product of parallax, diffuse and specular materials, scene motion, and illuminant variation. While decomposing all of these effects from a stack of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-25 Ilya Chugunov , David Shustin , Ruyu Yan , Chenyang Lei , Felix Heide