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A Top-Down Framework for Metric-Scale Athlete Localization from Single Broadcast Frames

Paper recorded by Signals 4 on 2026-09-02 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-02 on arXiv · recorded by Signals 4 on 2026-09-03

Category: cs.CV · 计算机视觉 · first seen 2026-09-03

Abstract

Accurate world-coordinate localization of athletes from single-frame broadcast footage is inherently challenging due to extreme scale disparities in ultra-high-resolution imagery. In this paper, we propose a top-down framework for metric-scale athlete localization from a single calibrated frame. Our approach centers on three key contributions. First, we propose Boundary-Aware Adaptive Tiling, a se

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#172 most recent of 237 cs.CV papers we have recorded · ↑ newer: MV-dVRK: A Multi-Viewpoint Benchmark for Spatial Surgical Perception · ↓ older: Generating Medical Image Counterfactuals using Causal Explanations
Cite this page: A Top-Down Framework for Metric-Scale Athlete Localization from Single Broadcast Frames: the #172 most recent of 237 cs.CV papers we have recorded (as of 2026-09-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-top-down-framework-for-metric-scale-athlete-localization-from-single-broadcast.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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