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Event cameras are dynamic vision sensors inspired by the biological retina, characterized by their high dynamic range, high temporal resolution, and low power consumption. These features make them capable of perceiving 3D environments even…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Hoonhee Cho , Jae-Young Kang , Kuk-Jin Yoon

Event cameras provide high dynamic range and microsecond-level temporal resolution, making them well-suited for indoor robot navigation, where conventional RGB cameras degrade under fast motion or low-light conditions. Despite advances in…

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

In comparison to conventional RGB cameras, the superior temporal resolution of event cameras allows them to capture rich information between frames, making them prime candidates for object tracking. Yet in practice, despite their…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Song Wang , Zhu Wang , Can Li , Xiaojuan Qi , Hayden Kwok-Hay So

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

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of asynchronous events. Despite having multiple advantages with…

Computer Vision and Pattern Recognition · Computer Science 2019-12-11 Stefano Pini , Guido Borghi , Roberto Vezzani

We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low-latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer…

Computer Vision and Pattern Recognition · Computer Science 2019-01-21 Daniel Gehrig , Henri Rebecq , Guillermo Gallego , Davide Scaramuzza

Recording fast motion in a high FPS (frame-per-second) requires expensive high-speed cameras. As an alternative, interpolating low-FPS videos from commodity cameras has attracted significant attention. If only low-FPS videos are available,…

Computer Vision and Pattern Recognition · Computer Science 2022-03-29 Weihua He , Kaichao You , Zhendong Qiao , Xu Jia , Ziyang Zhang , Wenhui Wang , Huchuan Lu , Yaoyuan Wang , Jianxing Liao

Video frame interpolation, the process of synthesizing intermediate frames between sequential video frames, has made remarkable progress with the use of event cameras. These sensors, with microsecond-level temporal resolution, fill…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Yuhan Liu , Yongjian Deng , Hao Chen , Bochen Xie , Youfu Li , Zhen Yang

We present the first event-based learning approach for motion segmentation in indoor scenes and the first event-based dataset - EV-IMO - which includes accurate pixel-wise motion masks, egomotion and ground truth depth. Our approach is…

Computer Vision and Pattern Recognition · Computer Science 2020-01-14 Anton Mitrokhin , Chengxi Ye , Cornelia Fermuller , Yiannis Aloimonos , Tobi Delbruck

Event cameras are promising devices for lowlatency tracking and high-dynamic range imaging. In this paper,we propose a novel approach for 6 degree-of-freedom (6-DoF)object motion tracking that combines measurements of eventand frame-based…

Computer Vision and Pattern Recognition · Computer Science 2022-04-11 Haolong Li , Joerg Stueckler

Current optical flow and point-tracking methods rely heavily on synthetic datasets. Event cameras are novel vision sensors with advantages in challenging visual conditions, but state-of-the-art frame-based methods cannot be easily adapted…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Friedhelm Hamann , Ziyun Wang , Ioannis Asmanis , Kenneth Chaney , Guillermo Gallego , Kostas Daniilidis

Event camera, a novel neuromorphic vision sensor, records data with high temporal resolution and wide dynamic range, offering new possibilities for accurate visual representation in challenging scenarios. However, event data is inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lin Zhu , Ruonan Liu , Xiao Wang , Lizhi Wang , Hua Huang

Event cameras are an interesting visual exteroceptive sensor that reacts to brightness changes rather than integrating absolute image intensities. Owing to this design, the sensor exhibits strong performance in situations of challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Runze Yuan , Tao Liu , Zijia Dai , Yi-Fan Zuo , Laurent Kneip

Video frame interpolation aims to generate high-quality intermediate frames from boundary frames and increase frame rate. While existing linear, symmetric and nonlinear models are used to bridge the gap from the lack of inter-frame motion,…

Computer Vision and Pattern Recognition · Computer Science 2023-05-19 Chenyang Shi , Hanxiao Liu , Jing Jin , Wenzhuo Li , Yuzhen Li , Boyi Wei , Yibo Zhang

Our paper proposes a direct sparse visual odometry method that combines event and RGB-D data to estimate the pose of agile-legged robots during dynamic locomotion and acrobatic behaviors. Event cameras offer high temporal resolution and…

Robotics · Computer Science 2023-05-17 Shifan Zhu , Zhipeng Tang , Michael Yang , Erik Learned-Miller , Donghyun Kim

Tracking transforming objects holds significant importance in various fields due to the dynamic nature of many real-world scenarios. By enabling systems accurately represent transforming objects over time, tracking transforming objects…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 You Wu , Yuelong Wang , Yaxin Liao , Fuliang Wu , Hengzhou Ye , Shuiwang Li

Event cameras asynchronously output low-latency event streams, promising for state estimation in high-speed motion and challenging lighting conditions. As opposed to frame-based cameras, the motion-dependent nature of event cameras presents…

Computer Vision and Pattern Recognition · Computer Science 2025-04-01 Peiyu Chen , Fuling Lin , Weipeng Guan , Peng Lu

Event-based cameras are biologically inspired sensors that output events, i.e., asynchronous pixel-wise brightness changes in the scene. Their high dynamic range and temporal resolution of a microsecond makes them more reliable than…

Robotics · Computer Science 2021-07-13 Antea Hadviger , Igor Cvišić , Ivan Marković , Sacha Vražić , Ivan Petrović

We then introduce a novel hierarchical knowledge distillation strategy that incorporates the similarity matrix, feature representation, and response map-based distillation to guide the learning of the student Transformer network. We also…

Computer Vision and Pattern Recognition · Computer Science 2025-02-11 Shiao Wang , Xiao Wang , Chao Wang , Liye Jin , Lin Zhu , Bo Jiang , Yonghong Tian , Jin Tang