Field Converter: Geometry-Initialized Temporal Residual Refinement for World-Grounded Player Pose Estimation from Soccer Broadcasts
Paper recorded by Signals 4 on 2026-09-09 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10
Category: cs.CV · 计算机视觉 · first seen 2026-09-10
Abstract
Recovering 3D human pose from monocular sports broadcasts remains challenging when players must be localized in a shared metric world coordinate system rather than only reconstructed relative to their own body. We introduce Field Converter, a geometry-initialized temporal residual framework for world-grounded 3D player pose estimation from calibrated soccer broadcasts. Our method first uses camera
Read on arXiv →
Cite this page: Field Converter: Geometry-Initialized Temporal Residual Refinement for World-Grounded Player Pose Estimation from Soccer Broadcasts: the #100 most recent of 237 cs.CV papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/field-converter-geometry-initialized-temporal-residual-refinement-for-world-grou.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable:
papers.json
Get 4 AI signals a day by email — free.
Get 4 AI signals a day by email — free