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Paper

Pixel-wise Regression: 3D Hand Pose Estimation via Spatial-form Representation and Differentiable Decoder

by Independent / Community 000b07e2b82a275a300be3d2d3755d84f4042e40

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 —

3D Hand pose estimation from a single depth image is an essential topic in computer vision and human-computer interaction. Although the rising of deep learning method boosts the accuracy a lot, the problem is still hard to solve due to the complex structure of the human hand. Existing methods with deep learning either lose spatial information of hand structure or lack a direct supervision of joint coordinates. In this paper, we propose a novel Pixel-wise Regression method, which use spatial-f...

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Semantic Scholar 8 Citations

Paper Information Summary
Entity Passport
Registry ID	000b07e2b82a275a300be3d2d3755d84f4042e40
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{000b07e2b82a275a300be3d2d3755d84f4042e40,
  author = {Unknown},
  title = {Pixel-wise Regression: 3D Hand Pose Estimation via Spatial-form Representation and Differentiable Decoder Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/000b07e2b82a275a300be3d2d3755d84f4042e40}},
  note = {Accessed via Free2AITools.}
}

APA Style

Unknown. (2026). Pixel-wise Regression: 3D Hand Pose Estimation via Spatial-form Representation and Differentiable Decoder [Paper]. Free2AITools. https://api.semanticscholar.org/000b07e2b82a275a300be3d2d3755d84f4042e40

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Full Specifications [+]

⚖️ 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

💬 Index Insight

FNI V2.0 for Pixel-wise Regression: 3D Hand Pose Estimation via Spatial-form Representation and Differentiable Decoder: Authority (A:75), Popularity (P:50), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

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HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

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📝 Executive Summary

"3D Hand pose estimation from a single depth image is an essential topic in computer vision and human-computer interaction. Although the rising of deep learning method boosts the accuracy a lot, the problem is still hard to solve due to the complex structure of the human hand. Existing methods with deep learning either lose spatial information of hand structure or lack a direct supervision of joint coordinates. In this paper, we propose a novel Pixel-wise Regression method, which use spatial-f..."

❝ Cite Node

@article{Unknown2026Pixel-wise,
  title={Pixel-wise Regression: 3D Hand Pose Estimation via Spatial-form Representation and Differentiable Decoder},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

🔗 Full Paper

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📊 Research Signals

📈8CitationsSemantic Scholar

🏛️75AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️vision multimediaField

🏷️ Research Topics

image generationvision models

📦Data Source: semantic_scholar

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🆔 Identity & Source

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

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
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downloads: 0
stars: null
forks: null
citations: 8

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