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

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Neuromorphic cameras, also known as event cameras, are asynchronous brightness-change sensors that can capture extremely fast motion without suffering from motion blur, making them particularly promising for 3D reconstruction in extreme…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Chuanzhi Xu , Langyi Chen , Haodong Chen , Vera Chung , Qiang Qu

We reconstruct 3D deformable object through time, in the context of a live pottery making process where the crafter molds the object. Because the object suffers from heavy hand interaction, and is being deformed, classical techniques cannot…

Computer Vision and Pattern Recognition · Computer Science 2019-08-06 Raoul de Charette , Sotiris Manitsaris

Event cameras are a new type of sensors that are different from traditional cameras. Each pixel is triggered asynchronously by event. The trigger event is the change of the brightness irradiated on the pixel. If the increment or decrement…

Computer Vision and Pattern Recognition · Computer Science 2022-03-24 Kun Xiao , Guohui Wang , Yi Chen , Jinghong Nan , Yongfeng Xie

Capturing a 3D human body is one of the important tasks in computer vision with a wide range of applications such as virtual reality and sports analysis. However, conventional frame cameras are limited by their temporal resolution and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Kai Kohyama , Shintaro Shiba , Yoshimitsu Aoki

In this work we present a novel approach for computing correspondences between non-rigid objects, by exploiting a reduced representation of deformation fields. Different from existing works that represent deformation fields by training a…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Ramana Sundararaman , Riccardo Marin , Emanuele Rodola , Maks Ovsjanikov

We present an approach to robustly track the geometry of an object that deforms over time from a set of input point clouds captured from a single viewpoint. The deformations we consider are caused by applying forces to known locations on…

Computer Vision and Pattern Recognition · Computer Science 2015-03-31 Stefanie Wuhrer , Jochen Lang , Motahareh Tekieh , Chang Shu

We propose a novel method to accurately reconstruct a set of images representing a single scene from few linear multi-view measurements. Each observed image is modeled as the sum of a background image and a foreground one. The background…

Computer Vision and Pattern Recognition · Computer Science 2013-09-19 Gilles Puy , Pierre Vandergheynst

Unlike traditional cameras which synchronously register pixel intensity, neuromorphic sensors only register `changes' at pixels where a change is occurring asynchronously. This enables neuromorphic sensors to sample at a micro-second level…

Computer Vision and Pattern Recognition · Computer Science 2024-08-29 Harbir Antil , Daniel Blauvelt , David Sayre

This paper presents an approach that reconstructs a hand-held object from a monocular video. In contrast to many recent methods that directly predict object geometry by a trained network, the proposed approach does not require any learned…

Computer Vision and Pattern Recognition · Computer Science 2022-12-01 Di Huang , Xiaopeng Ji , Xingyi He , Jiaming Sun , Tong He , Qing Shuai , Wanli Ouyang , Xiaowei Zhou

Event cameras are emerging imaging technology that offers advantages over conventional frame-based imaging sensors in dynamic range and sensing speed. Complementing the rich texture and color perception of traditional image frames, the…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Peiqi Duan , Boyu Li , Yixin Yang , Hanyue Lou , Minggui Teng , Yi Ma , Boxin Shi

This paper introduces the first differentiable simulator of event streams, i.e., streams of asynchronous brightness change signals recorded by event cameras. Our differentiable simulator enables non-rigid 3D tracking of deformable objects…

Computer Vision and Pattern Recognition · Computer Science 2021-05-03 Jalees Nehvi , Vladislav Golyanik , Franziska Mueller , Hans-Peter Seidel , Mohamed Elgharib , Christian Theobalt

Modeling Neural Radiance Fields for fast-moving deformable objects from visual data alone is a challenging problem. A major issue arises due to the high deformation and low acquisition rates. To address this problem, we propose to use event…

Computer Vision and Pattern Recognition · Computer Science 2023-09-26 Qi Ma , Danda Pani Paudel , Ajad Chhatkuli , Luc Van Gool

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. They offer significant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a…

Robotics · Computer Science 2019-01-21 Elias Mueggler , Guillermo Gallego , Henri Rebecq , Davide Scaramuzza

Event cameras are bio-inspired sensors that perform well in challenging illumination conditions and have high temporal resolution. However, their concept is fundamentally different from traditional frame-based cameras. The pixels of an…

Computer Vision and Pattern Recognition · Computer Science 2022-06-13 Xin Peng , Ling Gao , Yifu Wang , Laurent Kneip

Tracking non-rigidly deforming scenes using range sensors has numerous applications including computer vision, AR/VR, and robotics. However, due to occlusions and physical limitations of range sensors, existing methods only handle the…

Computer Vision and Pattern Recognition · Computer Science 2021-05-06 Yang Li , Hikari Takehara , Takafumi Taketomi , Bo Zheng , Matthias Nießner

Event-based structured light systems have recently been introduced as an exciting alternative to conventional frame-based triangulation systems for the 3D measurements of diffuse surfaces. Important benefits include the fast capture speed…

Computer Vision and Pattern Recognition · Computer Science 2025-06-12 Aniket Dashpute , Jiazhang Wang , James Taylor , Oliver Cossairt , Ashok Veeraraghavan , Florian Willomitzer

Non-rigid registration computes an alignment between a source surface with a target surface in a non-rigid manner. In the past decade, with the advances in 3D sensing technologies that can measure time-varying surfaces, non-rigid…

Computer Vision and Pattern Recognition · Computer Science 2022-03-18 Bailin Deng , Yuxin Yao , Roberto M. Dyke , Juyong Zhang

Visual object tracking under challenging conditions of motion and light can be hindered by the capabilities of conventional cameras, prone to producing images with motion blur. Event cameras are novel sensors suited to robustly perform…

Computer Vision and Pattern Recognition · Computer Science 2022-12-16 Irene Perez-Salesa , Rodrigo Aldana-Lopez , Carlos Sagues

In multi-view human body capture systems, the recovered 3D geometry or even the acquired imagery data can be heavily corrupted due to occlusions, noise, limited field of- view, etc. Direct estimation of 3D pose, body shape or motion on…

Computer Vision and Pattern Recognition · Computer Science 2018-02-02 Zhong Li , Yu Ji , Wei Yang , Jinwei Ye , Jingyi Yu

In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond…

Computer Vision and Pattern Recognition · Computer Science 2025-07-01 Timo Stoffregen , Guillermo Gallego , Tom Drummond , Lindsay Kleeman , Davide Scaramuzza