#self-supervised-learning (16 Repositories)
Ranked open-source repositories tagged with #self-supervised-learning, scored by pull request acceptance likelihood and maintainer engagement velocity.
28.8%
54.1h
16 repositories tagged #self-supervised-learning
open-edge-platform/geti
Build, train, optimize, and run computer vision models locally, from raw images to live inference. Open source, optimized for Intel XPU (CPU-only and CUDA also supported).
valeoai/Franca
Official code of Franca: Nested Matryoshka Clustering for Scalable Visual Representation Learning
prism-oncology/novae
Graph-based foundation model for spatial transcriptomics data. Zero-shot spatial domain inference, batch-effect correction, and many other features.
BigDataBiology/SemiBin
SemiBin: metagenomics binning with self-supervised deep learning
Optimization-AI/LibAUC
LibAUC: A Deep Learning Library for X-Risk Optimization
lightly-ai/lightly-train
All-in-one training for vision models (YOLO, ViTs, RT-DETR, DINOv3): pretraining, fine-tuning, distillation.
galilai-group/stable-pretraining
Reliable, minimal and scalable library for pretraining foundation and world models
alibaba/EasyCV
An all-in-one toolkit for computer vision
JiawangBian/sc_depth_pl
SC-Depth (V1, V2, and V3) for Unsupervised Monocular Depth Estimation Webpage:https://jiawangbian.github.io/sc_depth_pl/
MrGiovanni/ModelsGenesis
[MICCAI 2019 Young Scientist Award] [MedIA Best Paper Award] Models Genesis: self-supervised pre-training for 3D medical images. Learns transferable representations from unlabeled CT and MRI volumes, then fine-tunes for downstream segmentation and classification. Keras and PyTorch weights included.
ChandlerBang/awesome-self-supervised-gnn
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
MCG-NJU/VideoMAE
[NeurIPS 2022 Spotlight] VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training
facebookresearch/pixio
[CVPR 2026] Pixio: a capable vision encoder dedicated to dense prediction, simply by pixel reconstruction
lucidrains/byol-pytorch
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
Physics-Scaling/GeoPT
Official Code for "GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training" (ICML 2026) https://arxiv.org/pdf/2602.20399
Pang-Yatian/Point-MAE
[ECCV2022] Masked Autoencoders for Point Cloud Self-supervised Learning