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20232025
most citedTTPOINT: A Tensorized Point Cloud Network for Lightweight Action Recognition with Event Cameras

13 citations · 16 across the 9 of their papers we have counts for

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8 papers · 1 filter

cs.CV2025

SIS-Challenge: Event-based Spatio-temporal Instance Segmentation Challenge at the CVPR 2025 Event-based Vision Workshop

Friedhelm Hamann, Emil Mededovic, Fabian Gülhan +21

We present an overview of the Spatio-temporal Instance Segmentation (SIS) challenge held in conjunction with the CVPR 2025 Event-based Vision Workshop. The task is to predict accur…

cs.CV20251 cited

Event-Based Eye Tracking. 2025 Event-based Vision Workshop

Qinyu Chen, Chang Gao, Min Liu +29

This survey serves as a review for the 2025 Event-Based Eye Tracking Challenge organized as part of the 2025 CVPR event-based vision workshop. This challenge focuses on the task of…

cs.CV2025

Exploring Temporal Dynamics in Event-based Eye Tracker

Hongwei Ren, Xiaopeng Lin, Hongxiang Huang +2

Eye-tracking is a vital technology for human-computer interaction, especially in wearable devices such as AR, VR, and XR. The realization of high-speed and high-precision eye-track…

cs.CV2024

Event-based Motion Deblurring via Multi-Temporal Granularity Fusion

Xiaopeng Lin, Hongwei Ren, Yulong Huang +5

Conventional frame-based cameras inevitably produce blurry effects due to motion occurring during the exposure time. Event camera, a bio-inspired sensor offering continuous visual…

cs.CV20241 cited

FAPNet: An Effective Frequency Adaptive Point-based Eye Tracker

Xiaopeng Lin, Hongwei Ren, Bojun Cheng

Eye tracking is crucial for human-computer interaction in different domains. Conventional cameras encounter challenges such as power consumption and image quality during different…

cs.CV2024

Event-Based Eye Tracking. AIS 2024 Challenge Survey

Zuowen Wang, Chang Gao, Zongwei Wu +36

This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge. The task of the challenge focuses on processing eye movement recorded with event cameras and predicting t…