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CMU-Perceptual-Computing-Lab
openpose
C++2017–2023
CMU-Perceptual-Computing-Lab / openpose

openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

AI & Machine LearningLearning & ReferenceLibraries & SDKs
Explore on GitHubRead Hacker News discussions
15Distinct people
16Mentions
0Explicit recommenders
34.6KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

GitHub

Where it is used

No documented product use was verified in the last source check.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 7:56:55 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year16 dated mentions

Observed mentions: 2017-05-05 02:12:11 UTC to 2023-11-30 22:46:22 UTC.

02462017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 2 mentions; 2 submissions, 0 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 6 mentions; 1 submissions, 5 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2023

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC220
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC413
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC211
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC615
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC202

What Hacker News says

2 sources
netruk44·Nov 30, 2023
The input poses appear to be generated from OpenPose [0], which uses regular images as input. With the creation of stable diffusion video, you could theoretically prompt it to make a video of what you wanted, then run it through OpenPose. But I think the more realistic approach is to take a video of yourself doing the motions you want the AI to generate, and run that through OpenPose instead. Using just words leaves a lot to the model’s interpretation. I feel like you might wind up spending a lot of time manually fixing little things, similar to how you might infill the “wrong” parts of an AI generated image. It might be easier to just take a 15 second video to get the exact skeleton animation you want. [0] https://github.com/CMU-Perceptual-Computing-Lab/openpose
In Animate Anyone: Image-to-video synthesis for character animation

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