Movie Gen Bench - two media generation evaluation benchmarks released with Meta Movie Gen

Hackable and optimized Transformers building blocks, supporting a composable construction.

Code and models for the paper "The effectiveness of MAE pre-pretraining for billion-scale pretraining" https://arxiv.org/abs/2303.13496

Official implementation of MOST: Multiple object localization with self-supervised transformers published at ICCV 2023

Code and Models for "GeneCIS A Benchmark for General Conditional Image Similarity"

ImageBind One Embedding Space to Bind Them All

Code release for "Cut and Learn for Unsupervised Object Detection and Instance Segmentation" and "VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation"

[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

Masked Siamese Networks for Label-Efficient Learning (https://arxiv.org/abs/2204.07141)

Omnivore: A Single Model for Many Visual Modalities

Code release for "Detecting Twenty-thousand Classes using Image-level Supervision".

Code & Models for 3DETR - an End-to-end transformer model for 3D object detection

🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Code to reproduce the results in the FAIR research papers "Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples" https://arxiv.org/abs/…

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

PyTorch implementation of Barlow Twins.

DepthContrast self-supervised learning for 3D

VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

OpenMMLab Detection Toolbox and Benchmark

Audio Visual Instance Discrimination with Cross-Modal Agreement

An end-to-end PyTorch framework for image and video classification

Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

Scaling and Benchmarking Self-Supervised Visual Representation Learning

BISON: Binary Image SelectiON

Code used to generate synthetic scenes and bounding box annotations for object detection. This was used to generate data used in the Cut, Paste and Learn paper