13 citations · 20 across the 12 of their papers we have counts for
14 papers
Learning to Compute Is Not Learning to Retain or Reuse in Looped Transformers
Peilong Zhou, Hongtao Zhang, Yulong Huang +3
Looped transformers compute by applying one block repeatedly, so they can run for more loops than they were trained with. Recurrent reasoners are known to overthink: iterating past…
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…
SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba
Yulong Huang, Jianxiong Tang, Chao Wang +5
Large Language Models (LLMs) have achieved remarkable performance across tasks but remain energy-intensive due to dense matrix operations. Spiking neural networks (SNNs) improve en…
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…
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…
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…
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…
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…
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…