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A latent text-to-image diffusion model
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
This repository contains implementations and illustrative code to accompany DeepMind publications
Neural Networks: Zero to Hero
High-Resolution Image Synthesis with Latent Diffusion Models
TensorFlow Tutorials with YouTube Videos
PyTorch implementation of AnimeGANv2
VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images.
Repository for benchmarking graph neural networks (JMLR 2023)
[ICML 2024] Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs (RPG)
Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (http://fcn.berkeleyvision.org)
ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
Official implementation of Diffusion Autoencoders
Two time-scale update rule for training GANs
The official implementation of Autoregressive Image Generation using Residual Quantization (CVPR '22)
Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".
A mini-library for training consistency models.
PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)
Codebase for evaluation of deep generative models as presented in Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
Consistency models trained on CIFAR-10, in JAX.
PyTorch Implementations of Dropout Variants
Encoding position with the word embeddings.