# cure-lab/DeciWatch

<https://repo.masters-masters.com/en/repos/cure-lab/DeciWatch>

[Home](https://repo.masters-masters.com/en) › [cure-lab](https://repo.masters-masters.com/en/owners/cure-lab) › [DeciWatch](https://repo.masters-masters.com/en/repos/cure-lab/DeciWatch)

cure-lab/DeciWatch has 191 stars on GitHub. Its RepoMasters card: Prototype tier. \[ECCV 2022\] Official implementation of the paper "DeciWatch: A Simple…

| Field | Value |
| --- | --- |
| Owner | [cure-lab](https://repo.masters-masters.com/en/owners/cure-lab) |
| Stars | 191 |
| Forks | 15 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | Apache-2.0 |
| Created | 2022 |
| Topics | 2d-human-pose, 3d-pose-estimation, body-reconstruction, efficient-inference, human-pose-estimation, 3d-body-recovery, deep-learning, efficiency, efficient-neural-networks, pose-estimation |
| Tier | [Prototype (100 to 249 ★)](https://repo.masters-masters.com/en/ranks/rush) |
| View on GitHub | [cure-lab/DeciWatch](https://github.com/cure-lab/DeciWatch) |

## Repository

\[ECCV 2022\] Official implementation of the paper "DeciWatch: A Simple Baseline for 10x Efficient 2D and 3D Pose Estimation"

The tier for repos with 100 to 249 ★. Published odds per card pulled: 70%. Rarity: Common.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.