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Related papers: Event-based Non-Rigid Reconstruction from Contours

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This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild. Without requiring annotations of 3D mesh, 2D keypoints, or camera pose for each video frame, we pose…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Xueting Li , Sifei Liu , Shalini De Mello , Kihwan Kim , Xiaolong Wang , Ming-Hsuan Yang , Jan Kautz

Reconstructing Dynamic 3D Gaussian Splatting (3DGS) from low-framerate RGB videos is challenging. This is because large inter-frame motions will increase the uncertainty of the solution space. For example, one pixel in the first frame might…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Junhao He , Jiaxu Wang , Jia Li , Mingyuan Sun , Qiang Zhang , Jiahang Cao , Ziyi Zhang , Yi Gu , Jingkai Sun , Renjing Xu

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

Event cameras provide rich signals that are suitable for motion estimation since they respond to changes in the scene. As any visual changes in the scene produce event data, it is paramount to classify the data into different motions (i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Ryo Yamaki , Shintaro Shiba , Guillermo Gallego , Yoshimitsu Aoki

Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor' (APS), the `Dynamic and Active-pixel Vision Sensor'…

Computer Vision and Pattern Recognition · Computer Science 2020-11-13 Liyuan Pan , Richard Hartley , Cedric Scheerlinck , Miaomiao Liu , Xin Yu , Yuchao Dai

We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed motion capture due to bandwidth and dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ziyun Wang , Friedhelm Hamann , Kenneth Chaney , Wen Jiang , Guillermo Gallego , Kostas Daniilidis

Event-based imaging is a neurmorphic detection technique whereby an array of pixels detects a positive or negative change in light intensity at each pixel, and is hence particularly well suited to detecting motion. As compared to standard…

Instrumentation and Detectors · Physics 2022-09-16 Yugang Ren , Enrique Benedetto , Harry Borrill , Yelizaveta Savchuk , Molly Message , Katie O'Flynn , Muddassar Rashid , James Millen

Existing methods for 3D tracking from monocular RGB videos predominantly consider articulated and rigid objects. Modelling dense non-rigid object deformations in this setting remained largely unaddressed so far, although such effects can…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Soshi Shimada , Vladislav Golyanik , Patrick Pérez , Christian Theobalt

Reconstructing dynamic humans together with static scenes from monocular videos remains difficult, especially under fast motion, where RGB frames suffer from motion blur. Event cameras exhibit distinct advantages, e.g., microsecond temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-09-24 Xiaoting Yin , Hao Shi , Kailun Yang , Jiajun Zhai , Shangwei Guo , Lin Wang , Kaiwei Wang

We introduce a simple and effective method for retrieval of videos showing a specific event, even when the videos of that event were captured from significantly different viewpoints. Appearance-based methods fail in such cases, as…

Computer Vision and Pattern Recognition · Computer Science 2017-01-05 Gil Ben-Artzi , Michael Werman , Shmuel Peleg

We present the first method capable of photorealistically reconstructing deformable scenes using photos/videos captured casually from mobile phones. Our approach augments neural radiance fields (NeRF) by optimizing an additional continuous…

Computer Vision and Pattern Recognition · Computer Science 2021-09-13 Keunhong Park , Utkarsh Sinha , Jonathan T. Barron , Sofien Bouaziz , Dan B Goldman , Steven M. Seitz , Ricardo Martin-Brualla

Event sensors output a stream of asynchronous brightness changes (called ``events'') at a very high temporal rate. Previous works on recovering the lost intensity information from the event sensor data have heavily relied on the event…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Prasan A Shedligeri , Kaushik Mitra

Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic range and minimal motion blur. However, their output is not…

Computer Vision and Pattern Recognition · Computer Science 2024-04-08 Burak Ercan , Onur Eker , Aykut Erdem , Erkut Erdem

This paper presents a method which can track and 3D reconstruct the non-rigid surface motion of human performance using a moving RGB-D camera. 3D reconstruction of marker-less human performance is a challenging problem due to the large…

Computer Vision and Pattern Recognition · Computer Science 2018-10-10 Shafeeq Elanattil , Peyman Moghadam , Simon Denman , Sridha Sridharan , Clinton Fookes

A useful application of event sensing is visual odometry, especially in settings that require high-temporal resolution. The state-of-the-art method of contrast maximisation recovers the motion from a batch of events by maximising the…

Computer Vision and Pattern Recognition · Computer Science 2021-03-23 Daqi Liu , Alvaro Parra , Tat-Jun Chin

Recent years have seen the development of mature solutions for reconstructing deformable surfaces from a single image, provided that they are relatively well-textured. By contrast, recovering the 3D shape of texture-less surfaces remains an…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Jan Bednařík , Pascal Fua , Mathieu Salzmann

Real-time magnetic resonance imaging (MRI) methods generally shorten the measuring time by acquiring less data than needed according to the sampling theorem. In order to obtain a proper image from such undersampled data, the reconstruction…

Numerical Analysis · Mathematics 2013-12-05 Housen Li , Markus Haltmeier , Shuo Zhang , Jens Frahm , Axel Munk

In this paper, we address the problem of 3D object mesh reconstruction from RGB videos. Our approach combines the best of multi-view geometric and data-driven methods for 3D reconstruction by optimizing object meshes for multi-view…

Computer Vision and Pattern Recognition · Computer Science 2019-03-21 Chen-Hsuan Lin , Oliver Wang , Bryan C. Russell , Eli Shechtman , Vladimir G. Kim , Matthew Fisher , Simon Lucey

Pose estimation and tracking of objects is a fundamental application in 3D vision. Event cameras possess remarkable attributes such as high dynamic range, low latency, and resilience against motion blur, which enables them to address…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Zibin Liu , Banglei Guan , Yang Shang , Qifeng Yu , Laurent Kneip

Event cameras are bio-inspired cameras which can measure the change of intensity asynchronously with high temporal resolution. One of the event cameras' advantages is that they do not suffer from motion blur when recording high-speed…

Computer Vision and Pattern Recognition · Computer Science 2020-03-23 Chen Haoyu , Teng Minggui , Shi Boxin , Wang YIzhou , Huang Tiejun