The 2nd Anti-UAV Workshop & Challenge: Methods and Results
원문 초록
The 2nd Anti-UAV Workshop \& Challenge aims to encourage research in developing novel and accurate methods for multi-scale object tracking. The Anti-UAV dataset used for the Anti-UAV Challenge has been publicly released. There are two subsets in the dataset, $i.e.$, the test-dev subset and test-challenge subset. Both subsets consist of 140 thermal infrared video sequences, spanning multiple occurrences of multi-scale UAVs. Around 24 participating teams from the globe competed in the 2nd Anti-UAV Challenge. In this paper, we provide a brief summary of the 2nd Anti-UAV Workshop \& Challenge including brief introductions to the top three methods.The submission leaderboard will be reopened for researchers that are interested in the Anti-UAV challenge. The benchmark dataset and other information can be found at: https://anti-uav.github.io/.
함께 살펴볼 논문
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HiM2SAM: Enhancing SAM2 with Hierarchical Motion Estimation and Memory Optimization towards Long-term Tracking
UMDATrack: Unified Multi-Domain Adaptive Tracking Under Adverse Weather Conditions
Mamba-FETrack V2: Revisiting State Space Model for Frame-Event based Visual Object Tracking
Visual and Memory Dual Adapter for Multi-Modal Object Tracking
R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Tracking
토론
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