prog_gans_pytorch_inference This is an inference sample written in PyTorch of the original Theano/Lasagne code. I recreated the network as described in the paper of Karras et al. Since some layers seemed to be missing in PyTorch, these were implemented as well. The network and the layers can be found in model.py. For the demo, a 100-celeb-hq-1024×1024-ours snapshot was used, which was made publicly available by the authors. Since I couldn’t find any model converter between Theano/Lasagne and PyTorch, I used […]

LUPerson The repository is for our CVPR2021 paper Unsupervised Pre-training for Person Re-identification. LUPerson Dataset LUPerson is currently the largest unlabeled dataset for Person Re-identification, which is used for Unsupervised Pre-training. LUPerson consists of 4M images of over 200K identities and covers a much diverse range of capturing environments. Details can be found at ./LUP. Pre-trained Models Finetuned Results For MGN with ResNet50: Dataset mAP cmc1 path MSMT17 66.06/79.93 85.08/87.63 MSMT DukeMTMC 82.27/91.70 90.35/92.82 Duke Market1501 91.12/96.16 96.26/97.12 Market CUHK03-L […]

Nested-Co-teaching ([email protected]) Pytorch implementation of paper “Boosting Co-teaching with Compression Regularization for Label Noise” [PDF] If our project is helpful for your research, please consider citing : @inproceedings{chen2021boosting, title={Boosting Co-teaching with Compression Regularization for Label Noise}, author={Chen, Yingyi and Shen, Xi and Hu, Shell Xu and Suykens, Johan AK}, booktitle={CVPR Learning from Limited and Imperfect Data (L2ID) workshop}, year={2021} } Our model can be learnt in a single GPU GeForce GTX 1080Ti (12G), this code has been tested with Pytorch […]

Semi Hand-Object Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time (CVPR 2021). Installation Quick Demo (update soon) Training and Evaluation on HO3D Dataset Preparation Download the MANO model files (mano_v1_2.zip) from MANO website.Unzip and put mano/models/MANO_RIGHT.pkl into assets/mano_models. Download the YCB-Objectsused in HO3D dataset. Put unzipped folder object_models under assets. The structure should look like this: Semi-Hand-Object/ assets/ mano_models/ MANO_RIGHT.pkl object_models/ 006_mustard_bottle/ points.xyz textured_simple.obj …… Download and unzip HO3D datasetto path you like, the unzipped path is referred as […]

LaneAF LaneAF: Robust Multi-Lane Detection with Affinity Fields Installation Clone this repository Install Anaconda Create a virtual environment and install all dependencies: conda create -n laneaf pip python=3.6source activate laneafpip install numpy scipy matplotlib pillow scikit-learnpip install opencv-pythonpip install https://download.pytorch.org/whl/cu101/torch-1.7.0%2Bcu101-cp36-cp36m-linux_x86_64.whlpip install https://download.pytorch.org/whl/cu101/torchvision-0.8.1%2Bcu101-cp36-cp36m-linux_x86_64.whlsource deactivate You can alternately find your desired torch/torchvision wheel from here. Clone and make DCNv2: cd models/dlagit clone https://github.com/lbin/DCNv2.gitcd DCNv2./make.sh TuSimple The entire TuSimple dataset should be downloaded and organized as follows: └── TuSimple/ ├── clips/ | └── […]

HPRNet HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation Official PyTroch implementation of HPRNet. HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation,Nermin Samet, Emre Akbas,Under review. (arXiv pre-print) Highlights HPRNet is a bottom-up, one-stage and hierarchical keypoint regression method for whole-body pose estimation. HPRNet has the best performance among bottom-up methods for all the whole-body parts. HPRNet achieves SOTA performance for the face (76.0 AP) and hand (51.2 AP) keypoint estimation. Unlike two-stage methods, HPRNet predicts whole-body pose […]

The Python Workshop This is the repository for The Python Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish. Requirements and Setup To get started with the project files, you’ll need to: Install Jupyter on Windows, Mac, Linux Install Anaconda on Windows, Mac, Linux Install Docker About The Python Workshop More than just a Python guide for beginners, The Python Workshop takes you through the full spectrum of […]

Image Crop Analysis Code for reproducing our analysis in the paper titled: Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this code please cite our paper as follows: @ARTICLE{TwitterImageCrop2021, author = {{Yee}, Kyra and {Tantipongpipat}, Uthaipon and {Mishra}, Shubhanshu}, title = “{Image Cropping on Twitter: Fairness […]