Track-Anything VS openpose

Compare Track-Anything vs openpose and see what are their differences.

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Track-Anything openpose
16 36
6,113 29,902
- 0.9%
8.1 5.1
3 months ago 23 days ago
Python C++
MIT License GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Track-Anything

Posts with mentions or reviews of Track-Anything. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-11.

openpose

Posts with mentions or reviews of openpose. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-25.

What are some alternatives?

When comparing Track-Anything and openpose you can also consider the following projects:

stable-diffusion-webui - Stable Diffusion web UI

mediapipe - Cross-platform, customizable ML solutions for live and streaming media.

segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

AlphaPose - Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

sam-clip - Use Grounding DINO, Segment Anything, and CLIP to label objects in images.

detectron2 - Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model

mmpose - OpenMMLab Pose Estimation Toolbox and Benchmark.

sd-webui-segment-anything - Segment Anything for Stable Diffusion WebUI

lightweight-human-pose-estimation.pytorch - Fast and accurate human pose estimation in PyTorch. Contains implementation of "Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose" paper.

BlazePose-tensorflow - A third-party Tensorflow Implementation for paper "BlazePose: On-device Real-time Body Pose tracking".

MocapNET - We present MocapNET, a real-time method that estimates the 3D human pose directly in the popular Bio Vision Hierarchy (BVH) format, given estimations of the 2D body joints originating from monocular color images. Our contributions include: (a) A novel and compact 2D pose NSRM representation. (b) A human body orientation classifier and an ensemble of orientation-tuned neural networks that regress the 3D human pose by also allowing for the decomposition of the body to an upper and lower kinematic hierarchy. This permits the recovery of the human pose even in the case of significant occlusions. (c) An efficient Inverse Kinematics solver that refines the neural-network-based solution providing 3D human pose estimations that are consistent with the limb sizes of a target person (if known). All the above yield a 33% accuracy improvement on the Human 3.6 Million (H3.6M) dataset compared to the baseline method (MocapNET) while maintaining real-time performance