AI RESEARCH
SMART: SMPLest-X Mesh Adaptation and RAFT Tracking for Soccer Pose Estimation
arXiv CS.CV
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ArXi:2605.31551v1 Announce Type: new We present our approach to the FIFA Skeletal Tracking Challenge 2026, which requires estimating 3D world-space poses of soccer players from broadcast video. Our method finetunes SMPLest-X (ViT-H, 687M parameters) via a stratified clip split, multi-task depth supervision, and broadcast augmentation, paired with a RAFT dense optical flow camera tracker, foot-plane anchoring, and two-pass temporal smoothing.