UniPose
We propose UniPose, a unified framework for human pose estimation, based on our “Waterfall” Atrous Spatial Pooling architecture, that achieves state-of-art-results on several pose estimation metrics. Current pose estimation methods utilizing standard CNN architectures heavily rely on statistical postprocessing or predefined anchor poses for joint localization. UniPose incorporates contextual seg- mentation and joint localization to estimate the human pose in a single stage, with high accuracy, without relying on statistical postprocessing methods. The Waterfall module in UniPose leverages the efficiency of progressive filter- ing in the cascade architecture, while maintaining multi- scale fields-of-view comparable to spatial pyramid config- urations. Additionally, our method is extended to UniPose- LSTM for multi-frame processing and achieves state-of-the- art results for temporal pose estimation in Video. Our re- sults on multiple datase (by bmartacho)
tfjs
A WebGL accelerated JavaScript library for training and deploying ML models. (by tensorflow)
UniPose | tfjs | |
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1 | 30 | |
203 | 18,174 | |
- | 0.6% | |
0.0 | 8.6 | |
almost 2 years ago | 5 days ago | |
Python | TypeScript | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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.
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.
UniPose
Posts with mentions or reviews of UniPose.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-29.
tfjs
Posts with mentions or reviews of tfjs.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-04-09.
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JavaScript Libraries for Implementing Trendy Technologies in Web Apps in 2024
TensorFlow.js
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Deep Learning in JavaScript
Many people seem to be unaware of tensorflow.js, an official JS implementation of TF
https://github.com/tensorflow/tfjs
I'd love to see PyTorch in JS, but I think unless you get it running on the GPU it won't be able to do much.
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Machine Learning in NodeJS || Part 1: TensorflowJS Basics
TensorflowJS GitHub Repository
- PyTorch Primitives in WebGPU for the Browser
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I want to talk about WebGPU
Also, Tensorflow.js WebGPU backend has been in the works for quite some time: https://github.com/tensorflow/tfjs/tree/master/tfjs-backend-...
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WebGPU Fundamentals
It's a pity that tfjs never truly developed any decent ops. E.g. you need lgamma to implement the cap for zero-inflated poisson regression and tfjs simply doesn't have that: https://github.com/tensorflow/tfjs/issues/2011
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Chrome Ships WebGPU
People have been doing it for long with WebGL, see eg https://github.com/tensorflow/tfjs and https://cloudblogs.microsoft.com/opensource/2021/09/02/onnx-...
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How to get rotation (yaw/pitch/roll) from face detection keypoints?
thanks, no not unity, going to show it as a demo with threejs + tensorflow on the web. I found a github request to add face orientation https://github.com/tensorflow/tfjs/issues/3835 looks like they assigned someone to add it but doesn't look like its available yet, but there's some posts about the math I can use to get rotations based on some of the landmarks
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[P] Supporting neural network inference in web browsers
There already exist a wide variety of neural network inference engines that run in web browsers (e.g. TensorFlow.js and, my personal favorite for use with PyTorch models, ONNX Runtime Web), but pre- and post-processing has always required imperative manipulations on flat buffers rather than a clean ndarray interface.
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Tensorflow JS model crashing on mobile
Full docs and code: https://github.com/tensorflow/tfjs/tree/master/e2e/benchmarks/local-benchmark