Pinned Repositories
3D-GAN-pytorch
Responsible implementation of 3D-GAN NIPS 2016 paper:Learning a Probabilistic Latent Space of ObjectShapes via 3D Generative-Adversarial Modeling,that can be found https://papers.nips.cc/paper/6096-learning-a-probabilistic-latent-space-of-object-shapes-via-3d-generative-adversarial-modeling.pdf
3dmm_cnn
Regressing Robust and Discriminative 3D Morphable Models with a very Deep Neural Network
albumentations
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
challenge-iclr-2022
GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
geomstats
Computations and statistics on manifolds with geometric structures.
LEMO
Official Pytorch implementation for 2021 ICCV paper "Learning Motion Priors for 4D Human Body Capture in 3D Scenes" and trained models / data
libQGLViewer
libQGLViewer is an open source C++ library based on Qt that eases the creation of OpenGL 3D viewers.
Optimus
Optimus plugin was created to provide a testing environment for data-driven physics-based modeling.
Pixel2Mesh
Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images. In ECCV2018.
segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
sodabe622's Repositories
sodabe622/albumentations
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
sodabe622/geomstats
Computations and statistics on manifolds with geometric structures.
sodabe622/LEMO
Official Pytorch implementation for 2021 ICCV paper "Learning Motion Priors for 4D Human Body Capture in 3D Scenes" and trained models / data
sodabe622/Optimus
Optimus plugin was created to provide a testing environment for data-driven physics-based modeling.
sodabe622/segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
sodabe622/challenge-iclr-2022
GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021
sodabe622/animegan2-pytorch
PyTorch implementation of AnimeGANv2
sodabe622/ANOC
Official code for the paper "Leveraging Human Attention in Novel Object Captioning"
sodabe622/ar-cutpaste
Cut and paste your surroundings using AR
sodabe622/AR_Book_
sodabe622/awesome-computer-vision
A curated list of awesome computer vision resources
sodabe622/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
sodabe622/data-scientist-roadmap
Toturials coming with the "data science roadmap" picture.
sodabe622/DataScienceResources
Open Source Data Science Resources.
sodabe622/DeepPhysX
Interfacing AI with numerical simulation.
sodabe622/denoising-diffusion-pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
sodabe622/efficient-net-segmentation
Reference models and tools for Cloud TPUs.
sodabe622/eg3d
sodabe622/Final-project
Augmented Reality
sodabe622/GFPGAN
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
sodabe622/handcalcs
Python library for converting Python calculations into rendered latex.
sodabe622/MATLAB-Deep-Learning-Model-Hub
Discover pretrained models for deep learning in MATLAB
sodabe622/MixedRealityToolkit-Unity
This repository is for the legacy Mixed Reality Toolkit (MRTK) v2. For the latest version of the MRTK please visit https://github.com/MixedRealityToolkit/MixedRealityToolkit-Unity
sodabe622/ORB_SLAM2
Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities
sodabe622/PartImageNet
Introduction and scripts for the paper "PartImageNet: A Large, High-Quality Dataset of Parts" (Ju He, Shuo Yang, Shaokang Yang, Adam Kortylewski, Xiaoding Yuan, Jie-Neng Chen, Shuai Liu, Cheng Yang, Alan Yuille).
sodabe622/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
sodabe622/rgbdslam_v2
RGB-D SLAM for ROS
sodabe622/shap
A game theoretic approach to explain the output of any machine learning model.
sodabe622/text2mesh
3D mesh stylization driven by a text input in PyTorch
sodabe622/website