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Related papers: E3D: Event-Based 3D Shape Reconstruction

200 papers

Recently, Dynamic Vision Sensors (DVSs) sparked a lot of interest due to their inherent advantages over conventional RGB cameras. These advantages include a low latency, a high dynamic range and a low energy consumption. Nevertheless, the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-05 Katharina Bendig , René Schuster , Didier Stricker

Image-based three-dimensional (3D) reconstruction utilizes a set of photos to build 3D model and can be widely used in many emerging applications such as augmented reality (AR) and disaster recovery. Most of existing 3D reconstruction…

Networking and Internet Architecture · Computer Science 2020-07-06 Shuai Yu , Xu Chen , Shuai Wang , Lingjun Pu , Di Wu

3D reconstruction of deformable (or non-rigid) scenes from a set of monocular 2D image observations is a long-standing and actively researched area of computer vision and graphics. It is an ill-posed inverse problem, since -- without…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Edith Tretschk , Navami Kairanda , Mallikarjun B R , Rishabh Dabral , Adam Kortylewski , Bernhard Egger , Marc Habermann , Pascal Fua , Christian Theobalt , Vladislav Golyanik

Event cameras are novel sensors that output brightness changes in the form of a stream of asynchronous "events" instead of intensity frames. They offer significant advantages with respect to conventional cameras: high dynamic range (HDR),…

Computer Vision and Pattern Recognition · Computer Science 2020-04-02 Daniel Gehrig , Mathias Gehrig , Javier Hidalgo-Carrió , Davide Scaramuzza

We propose a generic event camera calibration framework using image reconstruction. Instead of relying on blinking LED patterns or external screens, we show that neural-network-based image reconstruction is well suited for the task of…

Computer Vision and Pattern Recognition · Computer Science 2021-05-27 Manasi Muglikar , Mathias Gehrig , Daniel Gehrig , Davide Scaramuzza

Active-stereo-based 3D shape measurement is crucial for various purposes, such as industrial inspection, reverse engineering, and medical systems, due to its strong ability to accurately acquire the shape of textureless objects. Active…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Ryo Furukawa , Kota Nishihara , Hiroshi Kawasaki

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

Event sensors offer high temporal resolution visual sensing, which makes them ideal for perceiving fast visual phenomena without suffering from motion blur. Certain applications in robotics and vision-based navigation require 3D perception…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Ethan Elms , Yasir Latif , Tae Ha Park , Tat-Jun Chin

Novel view synthesis from monocular videos of dynamic scenes with unknown camera poses remains a fundamental challenge in computer vision and graphics. While recent advances in 3D representations such as Neural Radiance Fields (NeRF) and 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-11-10 Mengqi Guo , Bo Xu , Yanyan Li , Gim Hee Lee

Reflective and textureless surfaces such as windows, mirrors, and walls can be a challenge for object and scene reconstruction. These surfaces are often poorly reconstructed and filled with depth discontinuities and holes, making it…

Computer Vision and Pattern Recognition · Computer Science 2021-10-07 Justin Wilson , Nicholas Rewkowski , Ming C. Lin , Henry Fuchs

The 3D reconstruction of objects is a prerequisite for many highly relevant applications of computer vision such as mobile robotics or autonomous driving. To deal with the inverse problem of reconstructing 3D objects from their 2D…

Computer Vision and Pattern Recognition · Computer Science 2021-12-09 Max Coenen , Franz Rottensteiner

3D vision is of paramount importance for numerous applications ranging from machine intelligence to precision metrology. Despite much recent progress, the majority of 3D imaging hardware remains bulky and complicated and provides much lower…

Computer Vision and Pattern Recognition · Computer Science 2025-02-12 Zicheng Shen , Feng Zhao , Yibo Ni , Yuanmu Yang

Event camera shows great potential in 3D hand pose estimation, especially addressing the challenges of fast motion and high dynamic range in a low-power way. However, due to the asynchronous differential imaging mechanism, it is challenging…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Jianping Jiang , Jiahe Li , Baowen Zhang , Xiaoming Deng , Boxin Shi

We present a technique for a complete 3D reconstruction of small objects moving in front of a textured background. It is a particular variation of multibody structure from motion, which specializes to two objects only. The scene is captured…

Computer Vision and Pattern Recognition · Computer Science 2021-05-25 Petr Hruby , Tomas Pajdla

Event cameras offer significant advantages, including a wide dynamic range, high temporal resolution, and immunity to motion blur, making them highly promising for addressing challenging visual conditions. Extracting and utilizing effective…

Computer Vision and Pattern Recognition · Computer Science 2025-08-05 Xin Dong , Yiwei Zhang , Yangjie Cui , Jinwu Xiang , Daochun Li , Zhan Tu

Our work aims to reconstruct a 3D object that is held and rotated by a hand in front of a static RGB camera. Previous methods that use implicit neural representations to recover the geometry of a generic hand-held object from multi-view…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Shijian Jiang , Qi Ye , Rengan Xie , Yuchi Huo , Xiang Li , Yang Zhou , Jiming Chen

Event cameras are a bio-inspired class of sensors that asynchronously measure per-pixel intensity changes. Under fixed illumination conditions in static or low-motion scenes, rigidly mounted event cameras are unable to generate any events…

Computer Vision and Pattern Recognition · Computer Science 2026-01-13 Vincenzo Polizzi , Stephen Yang , Quentin Clark , Jonathan Kelly , Igor Gilitschenski , David B. Lindell

A key question in the problem of 3D reconstruction is how to train a machine or a robot to model 3D objects. Many tasks like navigation in real-time systems such as autonomous vehicles directly depend on this problem. These systems usually…

Computer Vision and Pattern Recognition · Computer Science 2022-09-22 AmirHossein Zamani , Amir G. Aghdam , Kamran Ghaffari T

In this work, we address the task of 3D reconstruction in dynamic scenes, where object motions frequently degrade the quality of previous 3D pointmap regression methods, such as DUSt3R, that are originally designed for static 3D scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Jisang Han , Honggyu An , Jaewoo Jung , Takuya Narihira , Junyoung Seo , Kazumi Fukuda , Chaehyun Kim , Sunghwan Hong , Yuki Mitsufuji , Seungryong Kim

Event cameras record sparse illumination changes with high temporal resolution and high dynamic range. Thanks to their sparse recording and low consumption, they are increasingly used in applications such as AR/VR and autonomous driving.…

Computer Vision and Pattern Recognition · Computer Science 2024-01-24 Alberto Sabater , Luis Montesano , Ana C. Murillo