arXiv:2502.18867
Enhanced Transformer-Based Tracking for Skiing Events: Overcoming Multi-Camera Challenges, Scale Variations and Rapid Motion -- SkiTB Visual Tracking Challenge 2025
원문 초록
Accurate skier tracking is essential for performance analysis, injury prevention, and optimizing training strategies in alpine sports. Traditional tracking methods often struggle with occlusions, dynamic movements, and varying environmental conditions, limiting their effectiveness. In this work, we used STARK (Spatio-Temporal Transformer Network for Visual Tracking), a transformer-based model, to track skiers. We adapted STARK to address domain-specific challenges such as camera movements, camera changes, occlusions, etc. by optimizing the model's architecture and hyperparameters to better suit the dataset.
함께 살펴볼 논문
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R1-Track: Direct Application of MLLMs to Visual Object Tracking via Reinforcement Learning
Exploiting Lightweight Hierarchical ViT and Dynamic Framework for Efficient Visual Tracking
Towards Effective and Efficient Adversarial Defense with Diffusion Models for Robust Visual Tracking
CLDTracker: A Comprehensive Language Description for Visual Tracking
Efficient Motion Prompt Learning for Robust Visual Tracking
Towards Adaptive Meta-Gradient Adversarial Examples for Visual Tracking
토론
이 논문과 연결된 포럼 글이 아직 없습니다.