AI agents running research on single-GPU nanochat training automatically

A Docker-powered service for PDF document layout analysis. This service provides a powerful and flexible PDF analysis service. The service allows for the segmentation and classification of differen…

Official implementation of our MICCAI 2025 MLMI Workshop paper: “GRASPing Anatomy to Improve Pathology Segmentation.”

A project page template for academic papers. Demo at https://eliahuhorwitz.github.io/Academic-project-page-template/

The TTCP CAGE Challenges are a series of public challenges instigated to foster the development of autonomous cyber defensive agents. This CAGE Challenge 4 (CC4) returns to a defence industry enter…

BiomedParse: A Foundation Model for Joint Segmentation, Detection, and Recognition of Biomedical Objects Across Nine Modalities

[ICLR 2024 Oral] Supervised Pre-Trained 3D Models for Medical Image Analysis (9,262 CT volumes + 25 annotated classes)

🚀 Easy way to know how many visitors are viewing your Github, Website, Notion. 🎉

The official code for "SegVol: Universal and Interactive Volumetric Medical Image Segmentation".

[TMLR] A Comprehensive List of Works for Generative Modeling with Limited Data, Few Shots, and Zero Shot

A paper list of some recent Mamba-based CV works.

✨✨Latest Advances on Multimodal Large Language Models

Segment Anything Model for Medical Image Segmentation: Open-Source Project Summary

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

Refine high-quality datasets and visual AI models

[NeurIPS 2023] Release LMV-Med pre-trained models

MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet …

Universal Notation for Tensor Operations in Python

Diffusion Models in Medical Imaging (Published in Medical Image Analysis Journal)

A Pypi Package for Automated Segmentation of Anatomy in Chest Radiographs

nnDetection is a self-configuring framework for 3D (volumetric) medical object detection which can be applied to new data sets without manual intervention. It includes guides for 12 data sets that …

Automated lung segmentation in CT

SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners

Fully Convolutional Networks for Panoptic Segmentation (CVPR2021 Oral)

Panoramic Semantic Segmentation in the Wild

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…