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hodaeb's Projects

deep-high-resolution-net.pytorch icon deep-high-resolution-net.pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

dekr icon dekr

This is an official implementation of our CVPR 2021 paper "Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression" (https://arxiv.org/abs/2104.02300)

higherhrnet-human-pose-estimation icon higherhrnet-human-pose-estimation

This is an official implementation of our CVPR 2020 paper "HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimation" (https://arxiv.org/abs/1908.10357)

human-pose-estimation.pytorch icon human-pose-estimation.pytorch

The project is an official implement of our ECCV2018 paper "Simple Baselines for Human Pose Estimation and Tracking(https://arxiv.org/abs/1804.06208)"

imgclsmob icon imgclsmob

Sandbox for training deep learning networks

mpii-dataset-in-csv icon mpii-dataset-in-csv

Python Script to Convert .mat structured dataset of MPII Human Pose Annotations Dataset into .csv for more convenient understanding

pose-estimation icon pose-estimation

Easy to use SOTA Top-Down Multi-person Pose Estimation Models in PyTorch

pytorch-image-models icon pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-intermediatelayergetter icon pytorch-intermediatelayergetter

Simple easy to use module to get the intermediate values/activations from chosen Pytorch submodules. Supports submodule annidation and sequential modules.

transformer-in-transformer icon transformer-in-transformer

Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

transpose icon transpose

PyTorch Implementation for "TransPose: Keypoint localization via Transformer", ICCV 2021.

vit-pytorch icon vit-pytorch

Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)

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