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Reliable hand mesh reconstruction (HMR) from commonly-used color and depth sensors is challenging especially under scenarios with varied illuminations and fast motions. Event camera is a highly promising alternative for its high dynamic…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Jianping Jiang , Xinyu Zhou , Bingxuan Wang , Xiaoming Deng , Chao Xu , Boxin Shi

Event cameras, or Dynamic Vision Sensors (DVS) are novel neuromorphic sensors that capture brightness changes as a continuous stream of "events" rather than traditional intensity frames. Converting sparse events to dense intensity frames…

Computer Vision and Pattern Recognition · Computer Science 2024-11-13 Yuhan Bao , Lei Sun , Yuqin Ma , Kaiwei Wang

Achieving 3D reconstruction from images captured under optimal conditions has been extensively studied in the vision and imaging fields. However, in real-world scenarios, challenges such as motion blur and insufficient illumination often…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Xiaoting Yin , Hao Shi , Yuhan Bao , Zhenshan Bing , Yiyi Liao , Kailun Yang , Kaiwei Wang

We present EvDNeRF, a pipeline for generating event data and training an event-based dynamic NeRF, for the purpose of faithfully reconstructing eventstreams on scenes with rigid and non-rigid deformations that may be too fast to capture…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Anish Bhattacharya , Ratnesh Madaan , Fernando Cladera , Sai Vemprala , Rogerio Bonatti , Kostas Daniilidis , Ashish Kapoor , Vijay Kumar , Nikolai Matni , Jayesh K. Gupta

Object pose tracking is one of the pivotal technologies in multimedia, attracting ever-growing attention in recent years. Existing methods employing traditional cameras encounter numerous challenges such as motion blur, sensor noise,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-25 Zibin Liu , Banglei Guan , Yang Shang , Shunkun Liang , Zhenbao Yu , Qifeng Yu

Event-based cameras are bio-inspired sensors with pixels that independently and asynchronously respond to brightness changes at microsecond resolution, offering the potential to handle visual tasks in challenging scenarios. However, due to…

Computer Vision and Pattern Recognition · Computer Science 2026-02-25 Sheng Zhong , Zhongyang Ren , Xiya Zhu , Dehao Yuan , Cornelia Fermuller , Yi Zhou

Event-based cameras are biologically inspired sensors that output asynchronous pixel-wise brightness changes in the scene called events. They have a high dynamic range and temporal resolution of a microsecond, opposed to standard cameras…

Robotics · Computer Science 2019-07-18 Antea Hadviger , Ivan Marković , Ivan Petrović

Depth completion in dynamic scenes poses significant challenges due to rapid ego-motion and object motion, which can severely degrade the quality of input modalities such as RGB images and LiDAR measurements. Conventional RGB-D sensors…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Zhiqiang Yan , Jianhao Jiao , Zhengxue Wang , Gim Hee Lee

In low-light environments, conventional cameras often struggle to capture clear multi-view images of objects due to dynamic range limitations and motion blur caused by long exposure. Event cameras, with their high-dynamic range and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Jingqian Wu , Peiqi Duan , Zongqiang Wang , Changwei Wang , Boxin Shi , Edmund Y. Lam

Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report per-pixel intensity changes rather than outputting an actual intensity image at regular intervals. This new paradigm of image sensor offers…

Computer Vision and Pattern Recognition · Computer Science 2019-04-02 Yusuke Sekikawa , Kosuke Hara , Hideo Saito

Event cameras are bio-inspired sensors that perform well in HDR conditions and have high temporal resolution. However, different from traditional frame-based cameras, event cameras measure asynchronous pixel-level brightness changes and…

Computer Vision and Pattern Recognition · Computer Science 2022-03-09 Xin Peng , Yifu Wang , Ling Gao , Laurent Kneip

Dynamic vision sensors (DVS) are bio-inspired devices that capture visual information in the form of asynchronous events, which encode changes in pixel intensity with high temporal resolution and low latency. These events provide rich…

Computer Vision and Pattern Recognition · Computer Science 2025-01-03 Jingkai Sun , Qiang Zhang , Jiaxu Wang , Jiahang Cao , Renjing Xu

This paper presents a new event-based method for detecting and tracking features from the output of an event-based camera. Unlike many tracking algorithms from the computer vision community, this process does not aim for particular…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Laurent Dardelet , Sio-Hoi Ieng , Ryad Benosman

Capturing and reconstructing high-speed dynamic 3D scenes has numerous applications in computer graphics, vision, and interdisciplinary fields such as robotics, aerodynamics, and evolutionary biology. However, achieving this using a single…

Computer Vision and Pattern Recognition · Computer Science 2025-02-10 Zihao Zou , Ziyuan Qu , Xi Peng , Vivek Boominathan , Adithya Pediredla , Praneeth Chakravarthula

Event-based cameras are bio-inspired novel sensors that asynchronously record changes in illumination in the form of events, thus resulting in significant advantages over conventional cameras in terms of low power utilization, high dynamic…

Machine Learning · Statistics 2020-02-18 Lakshmi Annamalai , Anirban Chakraborty , Chetan Singh Thakur

Identifying independently moving objects is an essential task for dynamic scene understanding. However, traditional cameras used in dynamic scenes may suffer from motion blur or exposure artifacts due to their sampling principle. By…

Computer Vision and Pattern Recognition · Computer Science 2022-07-08 Yi Zhou , Guillermo Gallego , Xiuyuan Lu , Siqi Liu , Shaojie Shen

Event-based video reconstruction has garnered increasing attention due to its advantages, such as high dynamic range and rapid motion capture capabilities. However, current methods often prioritize the extraction of temporal information…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Lin Zhu , Yunlong Zheng , Yijun Zhang , Xiao Wang , Lizhi Wang , Hua Huang

Despite significant progress, RGB-based trackers remain vulnerable to challenging imaging conditions, such as low illumination and fast motion. Event cameras offer a promising alternative by asynchronously capturing pixel-wise brightness…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Shiao Wang , Xiao Wang , Duoqing Yang , Wenhao Zhang , Bo Jiang , Lin Zhu , Yonghong Tian , Bin Luo

2D cameras are often used in interactive systems. Other systems like gaming consoles provide more powerful 3D cameras for short range depth sensing. Overall, these cameras are not reliable in large, complex environments. In this work, we…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Mohamed Benkedadra , Matei Mancas , Sidi Ahmed Mahmoudi

This study introduces a novel approach to enhance the spatial-temporal resolution of time-event pixels based on luminance changes captured by event cameras. These cameras present unique challenges due to their low resolution and the sparse,…

Image and Video Processing · Electrical Eng. & Systems 2024-08-14 Waseem Shariff , Joe Lemley , Peter Corcoran