activity
20242026
collaborators

16 papers

cs.CV2026

SpikeOcc: Towards Resilient Multimodal 3D Occupancy Perception via Spiking Experts

Yiding Sun, Zijie Xu, Hongqiang Lin +7

Multimodal 3D occupancy prediction underpins safe autonomous driving through comprehensive scene understanding. However, existing methods have largely pursued higher accuracy throu…

cs.CV2026

Can We Perform Online RL for Image Editing without Editing Rewards?

Qichao Ma, Jikang Cheng, Ling Liang +3

Reinforcement learning (RL) enables direct preference optimization for image editing through editing-specific rewards, which remain less developed due to costly triplet supervision…

cs.NE2026

SpikingMOT: A Spike-Driven Multi-Object Tracker

Yiding Sun, Xiangyang Yang, Dongxu Zhang +7

Multi-object tracking (MOT) plays a fundamental role in visual perception, where accurate trajectory prediction is essential for reliable target association under complex motion pa…

cs.CV2026

Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval

Xintao Zong, Xian Zhong, Wenxuan Liu +3

Spiking neural networks (SNNs) have recently shown strong potential in unimodal visual and textual tasks, yet building a directly trained, low-energy, and high-performance SNN for…

cs.NE2026

General Self-Prediction Enhancement for Spiking Neurons

Zihan Huang, Zijie Xu, Yihan Huang +7

Spiking Neural Networks (SNNs) are highly energy-efficient due to event-driven, sparse computation, but their training is challenged by spike non-differentiability and trade-offs a…

cs.NE2025

Unleashing Temporal Capacity of Spiking Neural Networks through Spatiotemporal Separation

Yiting Dong, Zhaofei Yu, Jianhao Ding +2

Spiking Neural Networks (SNNs) are considered naturally suited for temporal processing, with membrane potential propagation widely regarded as the core temporal modeling mechanism.…

cs.CV2025

Driving in Spikes: An Entropy-Guided Object Detector for Spike Cameras

Ziyan Liu, Qi Su, Lulu Tang +2

Object detection in autonomous driving suffers from motion blur and saturation under fast motion and extreme lighting. Spike cameras, offer microsecond latency and ultra high dynam…

cs.CV2025

HAD: Hierarchical Asymmetric Distillation to Bridge Spatio-Temporal Gaps in Event-Based Object Tracking

Yao Deng, Xian Zhong, Wenxuan Liu +3

RGB cameras excel at capturing rich texture details with high spatial resolution, whereas event cameras offer exceptional temporal resolution and a high dynamic range (HDR). Levera…

cs.LG2025

: Online RL Fine-tuning for Flow-based Vision-Language-Action Models

Kang Chen, Zhihao Liu, Tonghe Zhang +11

Vision-Language-Action (VLA) models enable robots to understand and perform complex tasks from multimodal input. Although recent work explores using reinforcement learning (RL) to…

cs.RO2025

SpikeGrasp: A Benchmark for 6-DoF Grasp Pose Detection from Stereo Spike Streams

Zhuoheng Gao, Jiyao Zhang, Zhiyong Xie +5

Most robotic grasping systems rely on converting sensor data into explicit 3D point clouds, which is a computational step not found in biological intelligence. This paper explores…

cs.NE2025

PredNext: Explicit Cross-View Temporal Prediction for Unsupervised Learning in Spiking Neural Networks

Yiting Dong, Jianhao Ding, Zijie Xu +3

Spiking Neural Networks (SNNs), with their temporal processing capabilities and biologically plausible dynamics, offer a natural platform for unsupervised representation learning.…

cs.CV2025

SpikeStereoNet: A Brain-Inspired Framework for Stereo Depth Estimation from Spike Streams

Zhuoheng Gao, Yihao Li, Jiyao Zhang +7

Conventional frame-based cameras often struggle with stereo depth estimation in rapidly changing scenes. In contrast, bio-inspired spike cameras emit asynchronous events at microse…

cs.CV2025

SPKLIP: Aligning Spike Video Streams with Natural Language

Yongchang Gao, Meiling Jin, Zhaofei Yu +2

Spike cameras offer unique sensing capabilities but their sparse, asynchronous output challenges semantic understanding, especially for Spike Video-Language Alignment (Spike-VLA) w…

cs.CV2025

SOTA: Spike-Navigated Optimal TrAnsport Saliency Region Detection in Composite-bias Videos

Wenxuan Liu, Yao Deng, Kang Chen +3

Existing saliency detection methods struggle in real-world scenarios due to motion blur and occlusions. In contrast, spike cameras, with their high temporal resolution, significant…

cs.CV2025

SpikeDerain: Unveiling Clear Videos from Rainy Sequences Using Color Spike Streams

Hanwen Liang, Xian Zhong, Wenxuan Liu +4

Restoring clear frames from rainy videos presents a significant challenge due to the rapid motion of rain streaks. Traditional frame-based visual sensors, which capture scene conte…

cs.CV2024

Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks

Xian Zhong, Shengwang Hu, Wenxuan Liu +4

Spiking neural networks (SNNs) have garnered significant attention for their low power consumption and high biological interpretability. Their rich spatio-temporal information proc…