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Paper

AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements

by Independent / Community 00198e553085b28ad21788acb64935fc416808a6

Free2AITools Nexus Index

67.4

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 80

P: Popularity 56

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Image understanding is a foundational task in computer vision, with recent applications emerging in soccer posture analysis. However, existing publicly available datasets lack comprehensive information, notably in the form of posture sequences and 2D pose annotations. Moreover, current analysis models often rely on interpretable linear models (e.g., PCA and regression), limiting their capacity to capture non-linear spatiotemporal relationships in complex and diverse scenarios. To address thes...

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Semantic Scholar 23 Citations

Paper Information Summary
Entity Passport
Registry ID	00198e553085b28ad21788acb64935fc416808a6
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{00198e553085b28ad21788acb64935fc416808a6,
  author = {Unknown},
  title = {AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/00198e553085b28ad21788acb64935fc416808a6}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements [Paper]. Free2AITools. https://api.semanticscholar.org/00198e553085b28ad21788acb64935fc416808a6

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 80

Popularity (P) 56

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements: Authority (A:80), Popularity (P:56), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"Image understanding is a foundational task in computer vision, with recent applications emerging in soccer posture analysis. However, existing publicly available datasets lack comprehensive information, notably in the form of posture sequences and 2D pose annotations. Moreover, current analysis models often rely on interpretable linear models (e.g., PCA and regression), limiting their capacity to capture non-linear spatiotemporal relationships in complex and diverse scenarios. To address thes..."

❝ Cite Node

@article{Unknown2026AutoSoccerPose:,
  title={AutoSoccerPose: Automated 3D posture Analysis of Soccer Shot Movements},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

Free2AITools indexes the abstract and factual metadata for this paper. Read the complete, authoritative paper on the official source.

Read the full paper on arXiv

📊 Research Signals

📈23CitationsSemantic Scholar

🏛️80AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️vision multimediaField

🏷️ Research Topics

vision modelsimage generation

📦Data Source: semantic_scholar

🔄 Updated daily

Source summary: Based on semantic_scholar metadata. Not a recommendation.

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🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

source: semantic_scholar
author: Unknown
license: ArXiv
tags: paper, research, academic

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag

📊 Engagement & Metrics

downloads: 0
stars: null
forks: null
citations: 23

Data indexed from public sources. Updated daily.