English
Related papers

Related papers: Event-based Stereo Visual Odometry with Native Tem…

200 papers

We propose a continuous-time spline-based formulation for visual-inertial odometry (VIO). Specifically, we model the poses as a cubic spline, whose temporal derivatives are used to synthesize linear acceleration and angular velocity, which…

Robotics · Computer Science 2022-02-22 Jiawei Mo , Junaed Sattar

Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such as optical flow estimation. Most of the existing optical…

Computer Vision and Pattern Recognition · Computer Science 2022-11-18 Zhexiong Wan , Yuchao Dai , Yuxin Mao

We propose a novel deep visual odometry (VO) method that considers global information by selecting memory and refining poses. Existing learning-based methods take the VO task as a pure tracking problem via recovering camera poses from image…

Robotics · Computer Science 2020-08-05 Fei Xue , Xin Wang , Junqiu Wang , Hongbin Zha

We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation, and the displacements happen in an arbitrarily structured environment. As a result, the image matching…

Computer Vision and Pattern Recognition · Computer Science 2021-07-08 Yifu Wang , Jiaqi Yang , Xin Peng , Peng Wu , Ling Gao , Kun Huang , Jiaben Chen , Laurent Kneip

Dynamic Vision Sensors (DVS) capture event data with high temporal resolution and low power consumption, presenting a more efficient solution for visual processing in dynamic and real-time scenarios compared to conventional video capture…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Yiting Dong , Xiang He , Guobin Shen , Dongcheng Zhao , Yang Li , Yi Zeng

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

Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond latency and high dynamic range, capture brightness changes asynchronously, offering a unique…

Computer Vision and Pattern Recognition · Computer Science 2026-05-27 Rui Hu , Song Wu , Wen Yang , Jinjian Wu

Event based cameras are a new passive sensing modality with a number of benefits over traditional cameras, including extremely low latency, asynchronous data acquisition, high dynamic range and very low power consumption. There has been a…

Robotics · Computer Science 2018-02-21 Alex Zihao Zhu , Dinesh Thakur , Tolga Ozaslan , Bernd Pfrommer , Vijay Kumar , Kostas Daniilidis

Event cameras are bio-inspired vision sensors which measure per pixel brightness changes. They offer numerous benefits over traditional, frame-based cameras, including low latency, high dynamic range, high temporal resolution and low power…

Computer Vision and Pattern Recognition · Computer Science 2021-08-18 Simon Klenk , Jason Chui , Nikolaus Demmel , Daniel Cremers

Event cameras offer a high temporal resolution over traditional frame-based cameras, which makes them suitable for motion and structure estimation. However, it has been unclear how event-based 3D Gaussian Splatting (3DGS) approaches could…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Kai Kohyama , Yoshimitsu Aoki , Guillermo Gallego , Shintaro Shiba

We present a solution to the problem of spatio-temporal calibration for event cameras mounted on an onmi-directional vehicle. Different from traditional methods that typically determine the camera's pose with respect to the vehicle's body…

Robotics · Computer Science 2023-07-20 Xiao Li , Yi Zhou , Ruibin Guo , Xin Peng , Zongtan Zhou , Huimin Lu

Event cameras are bio-inspired sensors capable of providing a continuous stream of events with low latency and high dynamic range. As a single event only carries limited information about the brightness change at a particular pixel, events…

Computer Vision and Pattern Recognition · Computer Science 2020-09-21 Tobias Fischer , Michael Milford

Event-based cameras offer unique advantages such as high temporal resolution, high dynamic range, and low power consumption. However, the massive storage requirements and I/O burdens of existing synthetic data generation pipelines and the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Hanyue Lou , Jinxiu Liang , Minggui Teng , Yi Wang , Boxin Shi

Pose-based Video Anomaly Detection (VAD) has gained significant attention for its privacy-preserving nature and robustness to environmental variations. However, traditional frame-level evaluations treat video as a collection of isolated…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Narges Rashvand , Shanle Yao , Armin Danesh Pazho , Babak Rahimi Ardabili , Hamed Tabkhi

This paper introduces a robust framework for motion segmentation and egomotion estimation using event-based normal flow, tailored specifically for neuromorphic vision sensors. In contrast to traditional methods that rely heavily on optical…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zhiyuan Hua , Dehao Yuan , Cornelia Fermüller

Event-based sensors offer high temporal resolution and low latency by generating sparse, asynchronous data. However, converting this irregular data into dense tensors for use in standard neural networks diminishes these inherent advantages,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Aayush Atul Verma , Arpitsinh Vaghela , Bharatesh Chakravarthi , Kaustav Chanda , Yezhou Yang

Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low-frequency reference intensity information. These…

Computer Vision and Pattern Recognition · Computer Science 2018-11-02 Cedric Scheerlinck , Nick Barnes , Robert Mahony

Event cameras offer superior sensitivity to high-speed motion and extreme lighting, making event-based monocular depth estimation a promising approach for robust 3D perception in challenging conditions. However, progress is severely…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yinrui Ren , Jinjing Zhu , Kanghao Chen , Zhuoxiao Li , Jing Ou , Zidong Cao , Tongyan Hua , Peilun Shi , Yingchun Fu , Wufan Zhao , Hui Xiong

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

Maintaining stable and accurate localization during fast motion or on rough terrain remains highly challenging for mobile robots with onboard resources. Currently, multi-sensor fusion methods based on continuous-time representation offer a…

Robotics · Computer Science 2026-04-07 Lei Zhao , Xingyi Li , Tianchen Deng , Chuan Cao , Han Zhang , Weidong Chen