elifmeseci

elifmeseci's Stars

• TheAlgorithms/Python

  All Algorithms implemented in Python

  Language:Python184k5.9k1.5k44.3k

• facebookresearch/dinov2

  PyTorch code and models for the DINOv2 self-supervised learning method.

  Language:Jupyter Notebook8.8k95389763

• CASIA-IVA-Lab/FastSAM

  Fast Segment Anything

  Language:Python7.3k57203682

• MIC-DKFZ/nnUNet

  Language:Python5.6k772k1.7k

• roboflow/notebooks

  Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

  Language:Jupyter Notebook5.2k78130795

• cvg/LightGlue

  LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

  Language:Python3.3k48103319

• bowang-lab/MedSAM

  Segment Anything in Medical Images

  Language:Jupyter Notebook2.8k20275374

• HiLab-git/SSL4MIS

  Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

  Language:Python2.1k3786379

• wolny/pytorch-3dunet

  3D U-Net model for volumetric semantic segmentation written in pytorch

  Language:Jupyter Notebook2k360491

• HuCaoFighting/Swin-Unet

  [ECCVW 2022] The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"

  Language:Python1.7k12115304

• Hedlen/awesome-segment-anything

  Tracking and collecting papers/projects/others related to Segment Anything.

  1.5k6114130

• lxtGH/OMG-Seg

  OMG-LLaVA and OMG-Seg codebase

  Language:Python1.2k234447

• mhamilton723/STEGO

  Unsupervised Semantic Segmentation by Distilling Feature Correspondences

  Language:Jupyter Notebook7121496143

• yulequan/UA-MT

  code for MICCAI 2019 paper 'Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation'.

  Language:Python47252098

• rsummers11/CADLab

  Imaging Biomarkers and Computer-Aided Diagnosis Laboratory

  Language:C++4322934186

• kili-technology/kili-python-sdk

  Simplest and fastest image and text annotation tool.

  Language:Jupyter Notebook22792128

• nv-nguyen/cnos

  [ICCV 2023 R6D] PyTorch implementation of CNOS: A Strong Baseline for CAD-based Novel Object Segmentation based on Segmenting Anything and DINOv2

  Language:Python19142621

• itsprakhar/Downstream-Dinov2

  Downstream-Dino-V2: A GitHub repository featuring an easy-to-use implementation of the DINOv2 model by Facebook for downstream tasks such as Classification, Semantic Segmentation and Monocular depth estimation.

  Language:Jupyter Notebook17931111

• zhang-tao-whu/DVIS

  DVIS: Decoupled Video Instance Segmentation Framework

  Language:Python1234337

• Thanos-DB/FullyConvolutionalTransformer

  Official implementation of The Fully Convolutional Transformer for Medical Image Segmentation

  Language:Jupyter Notebook11432613

• HSG-AIML/SSLTransformerRS

  Code repository for "Self-supervised Vision Transformers for Land-cover Segmentation and Classification", CVPR EarthVision Workshop 2022 - Best Student Paper Award

  Language:Python796914

• vra/dinov2-retrieval

  A cli program of image retrieval using dinov2

  Language:Python55227

• diegovalsesia/speckle2void

  Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks

  Language:Jupyter Notebook542514

• xmed-lab/DHC

  MICCAI 2023: DHC: Dual-debiased Heterogeneous Co-training Framework for Class-imbalanced Semi-supervised Medical Image Segmentation

  Language:Python47390

• AghdamAmir/3D-UNet

  A pytorch implementation of 3D UNet for 3D MRI Segmentation.

  Language:Python38258

• wengzejia1/Semiformer

  Language:Python35355

• wenshuaizhao/MSSU-Net

  This code is for the paper "multi-scale supervised 3D U-Net for kidneys and kidney tumor segmentation".

  Language:Python27219

• ZhenYangCS/Mask2Former_DINOv2

  将Mask2Former的backbone替换成DINOv2训练好的ViT模型

  Language:Python25330

• tarolangner/ukb_segmentation

  PyTorch implementation for 2.5D U-Net segmentation of UK Biobank neck-to-knee body MRI

  Language:Python18403

• Aditya-Prakash-2108/Land-Cover-Assessment

  Proposed deep learning-based approach for land use classification in satellite imagery data, achieving 91.70% accuracy on 6 land cover classes using a CNN model trained on a large dataset

  Language:Jupyter Notebook1201