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Related papers: RoMo: Robust Motion Segmentation Improves Structur…

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Instance segmentation is a challenging task aiming at classifying and segmenting all object instances of specific classes. While two-stage box-based methods achieve top performances in the image domain, they cannot easily extend their…

Computer Vision and Pattern Recognition · Computer Science 2021-10-22 Xiang Li , Jinglu Wang , Xiao Li , Yan Lu

Observable motion in videos can give rise to the definition of objects moving with respect to the scene. The task of segmenting such moving objects is referred to as motion segmentation and is usually tackled either by aggregating motion…

Computer Vision and Pattern Recognition · Computer Science 2020-08-19 Amirhossein Kardoost , Kalun Ho , Peter Ochs , Margret Keuper

In this paper, we introduce a challenging task: extracting a fundamental matrix from a single motion blurred image. For a camera moving in 3D during exposure, the smear paths in the blurry image contain cues and constraints on this motion.…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Bao-Long Tran , Per-Erik Forssén , Fredrik Viksten

Referring video object segmentation (RVOS) aims to identify, track and segment the objects in a video based on language descriptions, which has received great attention in recent years. However, existing datasets remain focus on short video…

Computer Vision and Pattern Recognition · Computer Science 2025-10-29 Tianming Liang , Haichao Jiang , Yuting Yang , Chaolei Tan , Shuai Li , Wei-Shi Zheng , Jian-Fang Hu

Structure-from-Motion (SfM) is a fundamental 3D vision task for recovering camera parameters and scene geometry from multi-view images. While recent deep learning advances enable accurate Monocular Depth Estimation (MDE) from single images…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Shengjie Zhu , Ahmed Abdelkader , Mark J. Matthews , Xiaoming Liu , Wen-Sheng Chu

Rolling-shutter (RS) cameras are ubiquitous, but RS SfM (structure-from-motion) has not been fully solved yet. This work suggests an approach to remedy this: We characterize RS single-view geometry of observed world points or lines.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Sofía Errázuriz Muñoz , Kim Kiehn , Petr Hruby , Kathlén Kohn

Tackling image degradation due to atmospheric turbulence, particularly in dynamic environment, remains a challenge for long-range imaging systems. Existing techniques have been primarily designed for static scenes or scenes with small…

Computer Vision and Pattern Recognition · Computer Science 2024-04-23 Ripon Kumar Saha , Dehao Qin , Nianyi Li , Jinwei Ye , Suren Jayasuriya

Structure from Motion (SfM) techniques are being increasingly used to create 3D maps from images in many domains including environmental monitoring. However, SfM techniques are often confounded in visually repetitive environments as they…

Robotics · Computer Science 2022-01-11 Brian M. Hopkinson , Suchendra M. Bhandarkar

Segmentation of video objects in complex scenarios is highly challenging, and the MOSE dataset has significantly contributed to the development of this field. This technical report details the STSeg solution proposed by the "imaplus"…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Kehuan Song , Xinglin Xie , Kexin Zhang , Licheng Jiao , Lingling Li , Shuyuan Yang

Conventional structure-from-motion (SFM) research is primarily concerned with the 3D reconstruction of a single, rigidly moving object seen by a static camera, or a static and rigid scene observed by a moving camera --in both cases there…

Computer Vision and Pattern Recognition · Computer Science 2016-07-18 Suryansh Kumar , Yuchao Dai , Hongdong Li

We propose RoHM, an approach for robust 3D human motion reconstruction from monocular RGB(-D) videos in the presence of noise and occlusions. Most previous approaches either train neural networks to directly regress motion in 3D or learn…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Siwei Zhang , Bharat Lal Bhatnagar , Yuanlu Xu , Alexander Winkler , Petr Kadlecek , Siyu Tang , Federica Bogo

Event cameras provide a natural and data efficient representation of visual information, motivating novel computational strategies towards extracting visual information. Inspired by the biological vision system, we propose a behavior driven…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Nan Cai , Pia Bideau

In this paper, we show that transferring knowledge from other domains of video understanding combined with large-scale learning can improve robustness of Video Object Segmentation (VOS) under complex circumstances. Namely, we focus on…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Volodymyr Fedynyak , Yaroslav Romanus , Oles Dobosevych , Igor Babin , Roman Riazantsev

Real-time dense scene reconstruction during unstable camera motions is crucial for robotics, yet current RGB-D SLAM systems fail when cameras experience large viewpoint changes, fast motions, or sudden shaking. Classical optimization-based…

Robotics · Computer Science 2026-03-04 Siyan Dong , Zijun Wang , Lulu Cai , Yi Ma , Yanchao Yang

Deep learning-based visual perception models lack robustness when faced with camera motion perturbations in practice. The current certification process for assessing robustness is costly and time-consuming due to the extensive number of…

Machine Learning · Computer Science 2024-03-05 Hanjiang Hu , Zuxin Liu , Linyi Li , Jiacheng Zhu , Ding Zhao

Online reconstruction based on RGB-D sequences has thus far been restrained to relatively slow camera motions (<1m/s). Under very fast camera motion (e.g., 3m/s), the reconstruction can easily crumble even for the state-of-the-art methods.…

Computer Vision and Pattern Recognition · Computer Science 2021-05-13 Jiazhao Zhang , Chenyang Zhu , Lintao Zheng , Kai Xu

Video generation is experiencing rapid growth, driven by advances in diffusion models and the development of better and larger datasets. However, producing high-quality videos remains challenging due to the high-dimensional data and the…

Computer Vision and Pattern Recognition · Computer Science 2025-04-10 Elia Peruzzo , Dejia Xu , Xingqian Xu , Humphrey Shi , Nicu Sebe

Thin structures, such as wire-frame sculptures, fences, cables, power lines, and tree branches, are common in the real world. It is extremely challenging to acquire their 3D digital models using traditional image-based or depth-based…

Graphics · Computer Science 2020-05-21 Peng Wang , Lingjie Liu , Nenglun Chen , Hung-Kuo Chu , Christian Theobalt , Wenping Wang

Interactive autonomous applications require robustness of the perception engine to artifacts in unconstrained videos. In this paper, we examine the effect of camera motion on the task of action detection. We develop a novel ranking method…

Computer Vision and Pattern Recognition · Computer Science 2022-05-03 Burhan A. Mudassar , Sho Ko , Maojingjing Li , Priyabrata Saha , Saibal Mukhopadhyay

Structure from motion (SfM) enables us to reconstruct a scene via casual capture from cameras at different viewpoints, and novel view synthesis (NVS) allows us to render a captured scene from a new viewpoint. Both are hard with casual…

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