PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Last update: Oct 09, 2022

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Overview

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Release Notes

The official PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose, publish on NeuralIPS 2021.

Installation

To install required libs:

git clone https://github.com/Angtian/NeuralVS.git
cd NeuralVS
pip install -r requirements.txt

We use the same data preprocess as NeMo does. You can run the data preprocess part in NeMo repo or run the following code:

git clone https://github.com/Angtian/NeMo.git
cd NeMo
chmod +x PrepareData.sh
./PrepareData.sh
cd ..
mv ./NeMo/data ./

Matching using Single Image

Here we provide the code to run the pose matching experiment using single anchor image (section 4.3). To run the experiment using ImageNet pretrained backbone:

python .\code\SingleAnchorMatching.py --do_plot

To run the experiment with other backbone:

python .\code\SingleAnchorMatching.py --load_path {Path_to_saved_model} --do_plot

Code for Semi-supervised learning

Coming Soon

PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Related tags

Overview

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Release Notes

Installation

Matching using Single Image

Code for Semi-supervised learning

Owner

Angtian Wang

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PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Related tags

Overview

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose

Release Notes

Installation

Matching using Single Image

Code for Semi-supervised learning

Owner

Angtian Wang

Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert

HAR-stacked-residual-bidir-LSTMs - Deep stacked residual bidirectional LSTMs for HAR

A flexible ML framework built to simplify medical image reconstruction and analysis experimentation.

Pytorch implementation of TailCalibX : Feature Generation for Long-tail Classification

Simulation of the solar system using various nummerical methods

SBINN: Systems-biology informed neural network

An interactive DNN Model deployed on web that predicts the chance of heart failure for a patient with an accuracy of 98%

Image Restoration Using Swin Transformer for VapourSynth

Memory efficient transducer loss computation

RoBERTa Marathi Language model trained from scratch during huggingface 🤗 x flax community week

Code for paper entitled "Improving Novelty Detection using the Reconstructions of Nearest Neighbours"

Diverse graph algorithms implemented using JGraphT library.

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Web service for facial landmark detection, head pose estimation, facial action unit recognition, and eye-gaze estimation based on OpenFace 2.0

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