Official codebase for I-JEPA, the Image-based Joint-Embedding Predictive Architecture. First outlined in the CVPR paper, "Self-supervised learning from images with a joint-embedding predictive architecture."

Implementation of I-JEPA from "Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture"

This repo contains the code for the paper "Intuitive physics understanding emerges fromself-supervised pretraining on natural videos"

Experiments in Joint Embedding Predictive Architectures (JEPAs).

Audio-JEPA is an adaptation of the Joint-Embedding Predictive Architecture (JEPA) for self-supervised audio representation learning. Built upon the I-JEPA paradigm, it uses a Vision Transformer (ViT) backbone to predict latent representations of masked spectrogram patches.

A repository for paper Joint Embedding Predictive Architectures Focus on Slow Features

A toolkit for research on multimodal representation learning

Implementation of a JEPA Image World Model, trained on OpenAI's VPT Minecraft contractor dataset.

A simple repository to train I-JEPA from scratch

PyTorch implementation of I-JEPA

Implementation of VL JEPA Meta Research Paper

A simple and efficient implementation of Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture (I-JEPA)

No description available

Simple I-JEPA implementation for pre-training and fine-tuning your own datasets

I rebuild gpt2 but with jepa architecture

Mathematically more efficient alternative to I-JEPA

No description available

No description available

Reimplementation of Meta's I-JEPA work from scratch for fun.

An implementation of Facebook Research's iJEPA (Image Joint-Embedding Predictive Architecture) model for self-supervised learning on images using PyTorch

Final project repository for DS-GA-1008 class, need to create an encoder and pretrain it then it will act as an frozen encoder for the rest of the system similar to I-JEPA

From-scratch implementation of the I-JEPA

A PyTorch implementation of Meta AI's I-JEPA, a self-supervised learning framework for visual representations inspired by human-like prediction.

Based on https://github.com/facebookresearch/ijepa

My implementation of I-JEPA

Implementation of I-JEPA in Rust

Modified I-JEPA implementation on CIFAR-10

How to think about world models? I-JEPA, V-JEPA, V-JEPA2 and many more

Inspect and compare self-supervised vision model representations for DINOv2, I-JEPA, V-JEPA 2, EUPE

Self-supervised RGB-D multi-modalities framework that predicts missing depth features from RGB images using a Joint Embeddings Predictive Architecture with a variational latent space