13 citations · 19 across the 13 of their papers we have counts for
14 papers
Looped Transformers as Optimizers
Yulong Huang, Chen Jiang, Zhanpeng Zhou +5
Looped Transformers provide a parameter-efficient approach to depth scaling by repeatedly applying shared Transformer blocks. Recent reasoning models have likewise highlighted the…
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…
Exploring Data-Free LoRA Transferability for Video Diffusion Models
Yuchen Wang, Wenliang Zhong, Lichen Bai +6
Video diffusion models leveraging step distillation or causal distillation have achieved remarkable performance. However, adapting existing LoRAs to these variants remains a critic…
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…
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…
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…
Optical Spiking Neurons Enable High-Speed and Energy-Efficient Optical Neural Networks
Bo Xu, Zefeng Huang, Yuetong Fang +5
Optical neural networks (ONNs) perform extensive computations using photons instead of electrons, resulting in passively energy-efficient and low-latency computing. Among various O…
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…
A Simple and Effective Point-based Network for Event Camera 6-DOFs Pose Relocalization
Hongwei Ren, Jiadong Zhu, Yue Zhou +3
Event cameras exhibit remarkable attributes such as high dynamic range, asynchronicity, and low latency, making them highly suitable for vision tasks that involve high-speed motion…
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…
TTPOINT: A Tensorized Point Cloud Network for Lightweight Action Recognition with Event Cameras
Hongwei Ren, Yue Zhou, Haotian Fu +3
Event cameras have gained popularity in computer vision due to their data sparsity, high dynamic range, and low latency. As a bio-inspired sensor, event cameras generate sparse and…