activity
20222024
most citedThe Rise and Potential of Large Language Model Based Agents: A Survey

256 citations · 297 across the 24 of their papers we have counts for

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14 papers · 1 filter

cs.CV2024

Mamba-FETrack: Frame-Event Tracking via State Space Model

Ju Huang, Shiao Wang, Shuai Wang +3

RGB-Event based tracking is an emerging research topic, focusing on how to effectively integrate heterogeneous multi-modal data (synchronized exposure video frames and asynchronous…

cs.CV20242 cited

Spatio-Temporal Side Tuning Pre-trained Foundation Models for Video-based Pedestrian Attribute Recognition

Xiao Wang, Qian Zhu, Jiandong Jin +5

Existing pedestrian attribute recognition (PAR) algorithms are mainly developed based on a static image, however, the performance is unreliable in challenging scenarios, such as he…

cs.CV2024

Finding Visual Saliency in Continuous Spike Stream

Lin Zhu, Xianzhang Chen, Xiao Wang +1

As a bio-inspired vision sensor, the spike camera emulates the operational principles of the fovea, a compact retinal region, by employing spike discharges to encode the accumulati…

cs.CV20242 cited

CRSOT: Cross-Resolution Object Tracking using Unaligned Frame and Event Cameras

Yabin Zhu, Xiao Wang, Chenglong Li +5

Existing datasets for RGB-DVS tracking are collected with DVS346 camera and their resolution () is low for practical applications. Actually, only visible cameras ar…

cs.CV20231 cited

Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline

Xiao Wang, Shiao Wang, Chuanming Tang +4

Tracking using bio-inspired event cameras has drawn more and more attention in recent years. Existing works either utilize aligned RGB and event data for accurate tracking or direc…

cs.CV20231 cited

AMatFormer: Efficient Feature Matching via Anchor Matching Transformer

Bo Jiang, Shuxian Luo, Xiao Wang +2

Learning based feature matching methods have been commonly studied in recent years. The core issue for learning feature matching is to how to learn (1) discriminative representatio…