πŸ“„
Multi-view 3D human pose reconstruction based on spatial confidence point group for jump analysis in figure skating paper by Independent / Community
⭐ 65.1
πŸ“„
Paper

Multi-view 3D human pose reconstruction based on spatial confidence point group for jump analysis in figure skating

by Independent / Community 004c17e0662dbc2d3dd7eb01987ad1382c92e793
Free2AITools Nexus Index
65.1
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 75
P: Popularity 50
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

Competitive figure skaters perform successful jumps with critical parameters, which are valuable for jump analysis in athlete training. Driven by recent computer vision applications, recovering 3D pose of figure skater to obtain the meaningful variables has become increasingly important. However, conventional works have suffered from getting 3D information based on the corresponding 2D information directly or leaving the specificity of sports out of consideration. Issues such as self-occlusio...

Source β†’
Semantic Scholar 8 Citations
Paper Information Summary
Entity Passport
Registry ID 004c17e0662dbc2d3dd7eb01987ad1382c92e793
License ArXiv
Provider semantic_scholar
πŸ“œ

Cite this paper

Academic & Research Attribution

BibTeX 
@misc{004c17e0662dbc2d3dd7eb01987ad1382c92e793,
  author = {Unknown},
  title = {Multi-view 3D human pose reconstruction based on spatial confidence point group for jump analysis in figure skating Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/004c17e0662dbc2d3dd7eb01987ad1382c92e793}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). Multi-view 3D human pose reconstruction based on spatial confidence point group for jump analysis in figure skating [Paper]. Free2AITools. https://api.semanticscholar.org/004c17e0662dbc2d3dd7eb01987ad1382c92e793

πŸ”¬Technical Deep Dive

Full Specifications [+]

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 75
Popularity (P) 50
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Multi-view 3D human pose reconstruction based on spatial confidence point group for jump analysis in figure skating: Authority (A:75), Popularity (P:50), 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

πŸ“ Executive Summary

"Competitive figure skaters perform successful jumps with critical parameters, which are valuable for jump analysis in athlete training. Driven by recent computer vision applications, recovering 3D pose of figure skater to obtain the meaningful variables has become increasingly important. However, conventional works have suffered from getting 3D information based on the corresponding 2D information directly or leaving the specificity of sports out of consideration. Issues such as self-occlusio..."

❝ Cite Node 

@article{Unknown2026Multi-view,
  title={Multi-view 3D human pose reconstruction based on spatial confidence point group for jump analysis in figure skating},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

πŸ”— 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

πŸ“Š Research Signals

πŸ“ˆ8CitationsSemantic Scholar
πŸ›οΈ75AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈvision multimediaField

🏷️ Research Topics

vision models
πŸ“¦Data Source: semantic_scholar
πŸ”„ Updated daily

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

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

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

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

πŸ“Š Engagement & Metrics

downloads
0
stars
null
forks
null
citations
8

Data indexed from public sources. Updated daily.