4 citations · 9 across the 14 of their papers we have counts for
15 papers
DIMOS: Disentangling Instance-level Moving Object Segmentation
Hongxiang Huang, Hongwei Ren, Xiaopeng Lin +3
Moving instance segmentation (MIS) attracts increasing attention due to its broad applications in traffic surveillance, autonomous driving, and animal tracking. Event cameras recor…
MDN: Parallelizing Stepwise Momentum for Delta Linear Attention
Yulong Huang, Xiang Liu, Hongxiang Huang +5
Linear Attention (LA) offers a promising paradigm for scaling large language models (LLMs) to long sequences by avoiding the quadratic complexity of self-attention. Recent LA model…
PhysBrain: Human Egocentric Data as a Bridge from Vision Language Models to Physical Intelligence
Xiaopeng Lin, Shijie Lian, Bin Yu +10
Robotic generalization relies on physical intelligence: the ability to reason about state changes, contact-rich interactions, and long-horizon planning under egocentric perception…
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…
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…
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…
ClearSight: Human Vision-Inspired Solutions for Event-Based Motion Deblurring
Xiaopeng Lin, Yulong Huang, Hongwei Ren +4
Motion deblurring addresses the challenge of image blur caused by camera or scene movement. Event cameras provide motion information that is encoded in the asynchronous event strea…
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…
Scalable Event Cloud Network for Event-based Classification
Hongwei Ren, Fei Ma, Xiaopeng Lin +9
Event cameras are biologically inspired sensors garnering significant attention from both industry and academia. Mainstream methods favor frame and voxel representations, which rea…
PRF: Parallel Resonate and Fire Neuron for Long Sequence Learning in Spiking Neural Networks
Yulong Huang, Zunchang Liu, Changchun Feng +6
Recently, there is growing demand for effective and efficient long sequence modeling, with State Space Models (SSMs) proving to be effective for long sequence tasks. To further red…
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…
Rethinking Efficient and Effective Point-based Networks for Event Camera Classification and Regression: EventMamba
Hongwei Ren, Yue Zhou, Jiadong Zhu +7
Event cameras draw inspiration from biological systems, boasting low latency and high dynamic range while consuming minimal power. The most current approach to processing Event Clo…
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…
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Yulong Huang, Xiaopeng Lin, Hongwei Ren +5
Spiking neural networks (SNNs) are promising brain-inspired energy-efficient models. Compared to conventional deep Artificial Neural Networks (ANNs), SNNs exhibit superior efficien…
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition
Hongwei Ren, Yue Zhou, Yulong Huang +4
Event cameras are bio-inspired sensors that respond to local changes in light intensity and feature low latency, high energy efficiency, and high dynamic range. Meanwhile, Spiking…