mip-NeRF

Vision Transformer

This repository provides the official implementation of Vision Transformer (ViT) and MLP-Mixer architectures for image recognition, based on seminal research papers from Google Research. It includes pre-trained models on datasets like ImageNet and ImageNet-21k, along with code for fine-tuning on custom datasets using JAX and Flax. ## Key Features - **Vision Transformer (ViT)** — Applies transformer architecture to image patches for scalable image recognition. - **MLP-Mixer** — An all-MLP architecture for vision tasks, offering an alternative to convolutional networks. - **Pre-trained Models** — Includes a wide variety of ViT and Mixer models (e.g., ViT-B/16, ViT-L/16, Mixer-B/16) pre-trained on ImageNet and ImageNet-21k. - **Fine-tuning Support** — Provides configurable scripts to fine-tune models on datasets like CIFAR-10, CIFAR-100, and custom datasets. - **LiT Models** — Includes Locked-image text Tuning models for zero-shot transfer learning with image-text alignment. - **Cloud Integration** — Supports training on Google Cloud VMs with GPU or TPU accelerators. ## Philosophy The project emphasizes reproducibility and accessibility of state-of-the-art vision models, offering well-documented code and pre-trained checkpoints to facilitate research and practical applications in computer vision.

Big Transfer (BiT)

Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.

JAX RL

JAX (Flax) implementation of algorithms for Deep Reinforcement Learning with continuous action spaces.

NesT

Nested Hierarchical Transformer https://arxiv.org/pdf/2105.12723.pdf