disoley

disoley's Stars

• jacobgil/pytorch-grad-cam

  Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

  Language:Python11.3k444321.6k

• facebookresearch/dinov2

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

  Language:Jupyter Notebook10k96425907

• KevinMusgrave/pytorch-metric-learning

  The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

  Language:Python6.1k61521657

• facebookresearch/deit

  Official DeiT repository

  Language:Python4.2k46197565

• lightly-ai/lightly

  A python library for self-supervised learning on images.

  Language:Python3.3k28588290

• chiphuyen/dmls-book

  Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)

  2.6k477393

• mhamilton723/FeatUp

  Official code for "FeatUp: A Model-Agnostic Frameworkfor Features at Any Resolution" ICLR 2024

  Language:Jupyter Notebook1.5k167884

• facebookresearch/ToMe

  A method to increase the speed and lower the memory footprint of existing vision transformers.

  Language:Python1k1054171

• jacobgil/vit-explain

  Explainability for Vision Transformers

  Language:Python924626103

• AMLab-Amsterdam/AttentionDeepMIL

  Implementation of Attention-based Deep Multiple Instance Learning in PyTorch

  Language:Python8671721194

• khuyentran1401/data-science-template

  Template for a data science project

  Language:Python70799199

• immunogenomics/harmony

  Fast, sensitive and accurate integration of single-cell data with Harmony

  Language:R55924228102

• ssundaram21/dreamsim

  DreamSim: Learning New Dimensions of Human Visual Similarity using Synthetic Data (NeurIPS 2023 Spotlight) / / / / When Does Perceptual Alignment Benefit Vision Representations? (NeurIPS 2024)

  Language:Python457132425

• facebookresearch/mvit

  Code Release for MViTv2 on Image Recognition.

  Language:Python420142049

• ShirAmir/dino-vit-features

  Official implementation for the paper "Deep ViT Features as Dense Visual Descriptors".

  Language:Python41842151

• poolio/bilateral_solver

  Python code for the fast bilateral solver

  Language:Jupyter Notebook23119655

• sgvaze/generalized-category-discovery

  Code for our CVPR 2022 paper 'Generalized Category Discovery'. Project page: https://www.robots.ox.ac.uk/~vgg/research/gcd/

  Language:Python209132920

• hamidkazemi22/vit-visualization

  Language:Shell1834415

• jacobgil/pyfishervector

  Python implementation for Image Classification based on GMM dictionaries and fisher vectors.

  Language:Python1384957

• hila-chefer/RobustViT

  [NeurIPS 2022] Official PyTorch implementation of Optimizing Relevance Maps of Vision Transformers Improves Robustness. This code allows to finetune the explainability maps of Vision Transformers to enhance robustness.

  Language:Jupyter Notebook1274213

• okunator/cellseg_models.pytorch

  Encoder-Decoder Cell and Nuclei segmentation models

  Language:Python891204

• cfifty/CAML

  Language:Python6111811

• funkelab/cellulus

  Unsupervised Instance Segmentation in Microscopy

  Language:Python21422

• YiXXin/XCon

  XCon: Learning with Experts for Fine-grained Category Discovery

  Language:Python18301

• rssaketh/MOST

  Official implementation of MOST: Multiple object localization with self-supervised transformers published at ICCV 2023

  Language:Python17224

• stan-hua/CytoImageNet

  A large-scale pretraining dataset for bioimage transfer learning

  Language:Python14112

• cellimnet/microsnoop-publish

  Microsnoop: A generalist tool for microscopy image representation

  Language:Python8143

• SamriddhiJain/SimCLR-for-cell-profiling

  Codebase for: Contrastive Learning of Single-Cell Phenotypic Representations for Treatment Classification, MLMI 2021

  Language:Jupyter Notebook7222

• cfredinh/coda

  Language:Python410

• cfredinh/CDCL

  Repo for paper: Metadata-guided Consistency Learning for High Content Images

  Language:Python1