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Fully open reproduction of DeepSeek-R1
Official Pytorch Implementation for "MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation" presenting "MultiDiffusion" (ICML 2023)
[IJCV2024] Exploiting Diffusion Prior for Real-World Image Super-Resolution
[MICCAI 2023] MedNeXt is a fully ConvNeXt architecture for 3D medical image segmentation.
[ECCV 2024] SMFANet: A Lightweight Self-Modulation Feature Aggregation Network for Efficient Image Super-Resolution
Segment Anything in Medical Images
Official inference repo for FLUX.1 models
EMNLP'22 | MedCLIP: Contrastive Learning from Unpaired Medical Images and Texts
Fine-tuning CLIP using ROCO dataset which contains image-caption pairs from PubMed articles.
Large Language-and-Vision Assistant for Biomedicine, built towards multimodal GPT-4 level capabilities.
[ECCV2024] This is an official inference code of the paper "Glyph-ByT5: A Customized Text Encoder for Accurate Visual Text Rendering" and "Glyph-ByT5-v2: A Strong Aesthetic Baseline for Accurate Mu…
Official implementation code of the paper <AnyText: Multilingual Visual Text Generation And Editing>
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use th…
High-level DICOM abstractions for the Python programming language
pix2pix demo that learns from facial landmarks and translates this into a face
Awesome diffusion Video-to-Video (V2V). A collection of paper on diffusion model-based video editing, aka. video-to-video (V2V) translation. And a video editing benchmark code.
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
High Resolution CT Template Paper and Images
Foundational Models for State-of-the-Art Speech and Text Translation
Official repo for VGen: a holistic video generation ecosystem for video generation building on diffusion models
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
SOTA medical image segmentation methods based on various challenges
A collection of loss functions for medical image segmentation
[IEEE TMI] Official Implementation for UNet++