MedSAM2: Segment Anything in 3D Medical Images and Videos

[MICCAI'25] Regularized Low-Rank Adaptation for Few-Shot Organ Segmentation.

Official Code for "Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search"

⚡ Python-free Rust inference server — OpenAI-API compatible. GGUF + SafeTensors, hot model swap, auto-discovery, single binary. FREE now, FREE forever.

Microsoft BASIC for 6502 Microprocessor - Version 1.1

SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3

Official implementation for "Time-Contrastive Pretraining for In-Context Image and Video Segmentation", MICCAI 2025.

Origin code: https://github.com/Hhankyangg/sam-unet

Official repository for paper: "Mamba-3D as Masked Autoencoders for Accurate and Data-Efficient Analysis of Medical Ultrasound Videos"

H-Net: Hierarchical Network with Dynamic Chunking

Official code for "No time to train! Training-Free Reference-Based Instance Segmentation"

MICCAI 2023 - Asymmetric Contour Uncertainty Estimation for Medical Image Segmentation

[CVPR'25 Oral] MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision

try to export sam2 to onnx.

Using OnnxRuntime to inference yolov10,yolov10+SAM ,yolov10+bytetrack , SAM2 and paddleOCR by c++ .

[ICCV 2025] SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Pytorch implementation of MeanFlow on ImageNet and CIFAR10

JAX implementation of MeanFlow

Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.

[ICLR 2025 Spotlight] Official Implementation for ToST (Token Statistics Transformer)

Overview of architecture and implementation of TEDS-Net, as described in MICCAI 2021: "TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee TopologyPreservation in Segmentations"

Pytorch implementation for the paper titled "SimpleAR: Pushing the Frontier of Autoregressive Visual Generation"

[CVPR 2025] official implementation of “Exploring Intrinsic Normal Prototypes within a Single Image for Universal Anomaly Detection”