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

200 papers

This paper presents a novel method for the reconstruction of 3D edges in multi-view stereo scenarios. Previous research in the field typically relied on video sequences and limited the reconstruction process to either straight…

Computer Vision and Pattern Recognition · Computer Science 2018-01-18 Andrea Bignoli , Andrea Romanoni , Matteo Matteucci

Event cameras are bio-inspired sensors that output asynchronous and sparse event streams, instead of fixed frames. Benefiting from their distinct advantages, such as high dynamic range and high temporal resolution, event cameras have been…

Computer Vision and Pattern Recognition · Computer Science 2024-09-23 Zixin Zhang , Kanghao Chen , Lin Wang

Augmented reality devices require multiple sensors to perform various tasks such as localization and tracking. Currently, popular cameras are mostly frame-based (e.g. RGB and Depth) which impose a high data bandwidth and power usage. With…

Computer Vision and Pattern Recognition · Computer Science 2020-08-07 Etienne Dubeau , Mathieu Garon , Benoit Debaque , Raoul de Charette , Jean-François Lalonde

Event cameras are bio-inspired, motion-activated sensors that demonstrate substantial potential in handling challenging situations, such as motion blur and high-dynamic range. In this paper, we proposed EVI-SAM to tackle the problem of 6…

Computer Vision and Pattern Recognition · Computer Science 2024-05-24 Weipeng Guan , Peiyu Chen , Huibin Zhao , Yu Wang , Peng Lu

Event cameras are novel sensors that report brightness changes in the form of asynchronous "events" instead of intensity frames. They have significant advantages over conventional cameras: high temporal resolution, high dynamic range, and…

Computer Vision and Pattern Recognition · Computer Science 2019-04-18 Henri Rebecq , René Ranftl , Vladlen Koltun , Davide Scaramuzza

3D hand pose estimation from monocular videos is a long-standing and challenging problem, which is now seeing a strong upturn. In this work, we address it for the first time using a single event camera, i.e., an asynchronous vision sensor…

Computer Vision and Pattern Recognition · Computer Science 2021-10-12 Viktor Rudnev , Vladislav Golyanik , Jiayi Wang , Hans-Peter Seidel , Franziska Mueller , Mohamed Elgharib , Christian Theobalt

Event-based cameras are becoming increasingly popular for their ability to capture high-speed motion with low latency and high dynamic range. However, generating videos from events remains challenging due to the highly sparse and varying…

Computer Vision and Pattern Recognition · Computer Science 2024-03-19 Burak Ercan , Onur Eker , Canberk Saglam , Aykut Erdem , Erkut Erdem

The bio-inspired event cameras or dynamic vision sensors are capable of asynchronously capturing per-pixel brightness changes (called event-streams) in high temporal resolution and high dynamic range. However, the non-structural…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 Qiang Qu , Yiran Shen , Xiaoming Chen , Yuk Ying Chung , Tongliang Liu

We propose a method for 3D object reconstruction and 6D-pose estimation from 2D images that uses knowledge about object shape as the primary key. In the proposed pipeline, recognition and labeling of objects in 2D images deliver 2D segment…

Computer Vision and Pattern Recognition · Computer Science 2022-03-03 Marcell Wolnitza , Osman Kaya , Tomas Kulvicius , Florentin Wörgötter , Babette Dellen

Scene reconstruction from casually captured videos has wide applications in real-world scenarios. With recent advancements in differentiable rendering techniques, several methods have attempted to simultaneously optimize scene…

Computer Vision and Pattern Recognition · Computer Science 2025-11-03 Bohao Liao , Wei Zhai , Zengyu Wan , Zhixin Cheng , Wenfei Yang , Tianzhu Zhang , Yang Cao , Zheng-Jun Zha

Event cameras provide microsecond latency, making them suitable for 6D object pose tracking in fast, dynamic scenes where conventional RGB and depth pipelines suffer from motion blur and large pixel displacements. We introduce EventTrack6D,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-07 Jae-Young Kang , Hoonhee Cho , Taeyeop Lee , Minjun Kang , Bowen Wen , Youngho Kim , Kuk-Jin Yoon

The emergence of neural radiance fields (NeRF) and 3D Gaussian splatting (3DGS) has advanced novel view synthesis (NVS). These methods, however, require high-quality RGB inputs and accurate corresponding poses, limiting robustness under…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Yunsoo Kim , Changki Sung , Dasol Hong , Hyun Myung

In this paper, we propose an approach to address the problem of 3D reconstruction of scenes from a single image captured by a light-field camera equipped with a rolling shutter sensor. Our method leverages the 3D information cues present in…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Hermes McGriff , Renato Martins , Nicolas Andreff , Cédric Demonceaux

Event cameras sense intensity changes and have many advantages over conventional cameras. To take advantage of event cameras, some methods have been proposed to reconstruct intensity images from event streams. However, the outputs are still…

Computer Vision and Pattern Recognition · Computer Science 2020-03-18 Lin Wang , Tae-Kyun Kim , Kuk-Jin Yoon

Continuous video monitoring in surveillance, robotics, and wearable systems faces a fundamental power constraint: conventional RGB cameras consume substantial energy through fixed-rate capture. Event cameras offer sparse, motion-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Dmitrii Torbunov , Onur Okuducu , Yi Huang , Odera Dim , Rebecca Coles , Yonggang Cui , Yihui Ren

Event camera is an emerging imaging sensor for capturing dynamics of moving objects as events, which motivates our work in estimating 3D human pose and shape from the event signals. Events, on the other hand, have their unique challenges:…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Shihao Zou , Chuan Guo , Xinxin Zuo , Sen Wang , Pengyu Wang , Xiaoqin Hu , Shoushun Chen , Minglun Gong , Li Cheng

Event cameras provide a promising sensing modality for high-speed and high-dynamic-range vision by asynchronously capturing brightness changes. A fundamental task in event-based vision is event-to-video (E2V) reconstruction, which aims to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Jingqian Wu , Yunbo Jia , Shengpeng Xu , Edmund Y. Lam

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

Event cameras respond to brightness changes in the scene asynchronously and independently for every pixel. Due to the properties, these cameras have distinct features: high dynamic range (HDR), high temporal resolution, and low power…

Computer Vision and Pattern Recognition · Computer Science 2022-10-17 Jongwan Kim , DongJin Lee , Byunggook Na , Seongsik Park , Jeonghee Jo , Sungroh Yoon

Humans build 3D understandings of the world through active object exploration, using jointly their senses of vision and touch. However, in 3D shape reconstruction, most recent progress has relied on static datasets of limited sensory data…

Computer Vision and Pattern Recognition · Computer Science 2021-10-27 Edward J. Smith , David Meger , Luis Pineda , Roberto Calandra , Jitendra Malik , Adriana Romero , Michal Drozdzal