una-dinosauria/3d-pose-baseline

Health v2 · maintenance only

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Adoption not part of the score

1459 stars · 357 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A TensorFlow implementation of a simple yet effective baseline for 3D human pose estimation from 2D keypoints, published at ICCV 2017. It includes training, evaluation, and visualization code on the Human3.6M dataset.

Use cases

• estimate 3d human pose from 2d keypoints
• reproduce the iccv 2017 3d pose baseline results
• train a pose lifting model on human3.6m
• benchmark my 3d pose estimation model against a baseline
• visualize 3d human skeleton poses from video
• learn how 2d-to-3d pose lifting works

When to choose

• you need a well-known, citable baseline for 2D-to-3D human pose lifting
• you are working with the Human3.6M dataset and ground-truth 2D detections
• you want compact, readable research code to build upon

When to avoid

• you need state-of-the-art accuracy on modern benchmarks
• you require 2D detections from an external detector (SH detections are no longer supported)
• you need TensorFlow 2.x or actively maintained code

Facets

library · maturity maintenance

machine-learning computer-vision deep-learning computer-vision machine-learning deep-learning python 3d-pose-estimation human-pose tensorflow iccv-2017 research-code human36m gpu

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markdown · JSON · MCP: product_card(name="una-dinosauria/3d-pose-baseline")