MedSAM3: Delving into Segment Anything with Medical Concepts

Official PyTorch Implementation of FS-SAM2

Official code of "EVF-SAM: Early Vision-Language Fusion for Text-Prompted Segment Anything Model"

Contrastive Language-Image Forensic Search allows free text searching through videos using OpenAI's machine learning model CLIP

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

Run Segment Anything Model 2 on a live video stream

Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts

Medical SAM 2: Segment 3D Medical Images Via Segment Anything Model 2

[NeurIPS 2024 Workshop AIM-FM] Official code implementation for paper: Surgical SAM 2

Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"

[AAAI' 25] U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation

We developed a python UI based on labelme and segment-anything for pixel-level annotation. It support multiple masks generation by SAM(box/point prompt), efficient polygon modification and category…

🏆1st place in the MICCAI challenge CrossMoDA 2023

Only implemented through torch: "bi - mamba2" , "vision- mamba2 -torch". support 1d/2d/3d/nd and support export by jit.script/onnx;

This is the implementation of Cross-attention inspired Mamba.

[WACV 2025] SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

[ECCV'20] Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation (code&data-processing pipeline)

[AAAI 25] FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image Segmentation

The pytorch implementation of Position-Aware Relation Networks (PARN), which is proposed in Position-Aware Relation Networks for Few-Shot Learning.

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

Code for our ICCV 2019 paper PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment

Implementation of the methods described in "Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation", ECCV 2022

Learning Continuous Signed Distance Functions for Shape Representation

Few Shot Semantic Segmentation Papers

PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation (TPAMI).

Dual Contrastive Learning for Few-shot Medical Image Segmentation

Self-Supervised Generative Style Transfer for One-Shot Medical Image Segmentation

an image registration/augmentation/segmentation package