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Tensors and Dynamic neural networks in Python with strong GPU acceleration
Models and examples built with TensorFlow
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
PyTorch Tutorial for Deep Learning Researchers
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
End-to-End Object Detection with Transformers
StyleGAN2 - Official TensorFlow Implementation
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Geometric Computer Vision Library for Spatial AI
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.
Benchmarks of approximate nearest neighbor libraries in Python
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
A PyTorch Library for Accelerating 3D Deep Learning Research
Code for robust monocular depth estimation described in "Ranftl et. al., Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer, TPAMI 2022"
Google Drive Public File Downloader when Curl/Wget Fails
Python package for the evaluation of odometry and SLAM
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)