minnkyungkim

minnkyungkim's Stars

• facebookresearch/segment-anything

  The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook47k3056625.6k

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  26.6k287412.2k

• matterport/Mask_RCNN

  Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

  Language:Python24.6k5812.8k11.7k

• karpathy/minGPT

  A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

  Language:Python19.9k255722.5k

• lucidrains/vit-pytorch

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

  Language:Python19.9k1522653k

• google-deepmind/alphafold

  Open source code for AlphaFold.

  Language:Python12.4k2208502.2k

• facebookresearch/pytorch3d

  PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

  Language:Python8.7k1481.6k1.3k

• cxli233/FriendsDontLetFriends

  Friends don't let friends make certain types of data visualization - What are they and why are they bad.

  Language:R6.3k1117231

• autonomousvision/giraffe

  This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"

  Language:Python1.2k2157160

• apchenstu/TensoRF

  [ECCV 2022] Tensorial Radiance Fields, a novel approach to model and reconstruct radiance fields

  Language:Python1.2k2172153

• allenai/visprog

  Official code for VisProg (CVPR 2023 Best Paper!)

  Language:Python686151864

• jonbarron/robust_loss_pytorch

  A pytorch port of google-research/google-research/robust_loss/

  Language:Python659133288

• deel-ai/xplique

  👋 Xplique is a Neural Networks Explainability Toolbox

  Language:Python628117050

• lahoud/3d-vision-transformers

  A list of 3D computer vision papers with Transformers

  39913030

• rmaphoh/RETFound_MAE

  RETFound - A foundation model for retinal image

  Language:Jupyter Notebook342152976

• google/explaining-in-style

  Language:Jupyter Notebook2198328

• nadeemlab/DeepLIIF

  Deep Learning Inferred Multiplex ImmunoFluorescence for IHC Image Quantification (https://deepliif.org) [Nature Machine Intelligence'22, CVPR'22, MICCAI'23, Histopathology'23, MICCAI'24]

  Language:Python16661961

• namepllet/HandOccNet

  Offical pytorch implementation of "HandOccNet: Occlusion-Robust 3D Hand Mesh Estimation Network", CVPR 2022.

  Language:Python15523430

• LengerichLab/CompBioDatasetsForMachineLearning

  A Curated List of Computational Biology Datasets Suitable for Machine Learning

  1519023

• WellyZhang/RAVEN

  RAVEN: A Dataset for Relational and Analogical Visual rEasoNing

  Language:Python1517629

• AdamKortylewski/CompositionalNets

  Official implementation of CVPR2020 paper: "Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion" https://arxiv.org/abs/2003.04490

  Language:Python11321224

• adelekuzmiakova/pytorch3d-renderer

  A PyTorch3D walkthrough and a Medium article 👋 on how to render 3D .obj meshes from various viewpoints to create 2D images.

  Language:Jupyter Notebook952113

• jusiro/FLAIR

  FLAIR: A Foundation LAnguage-Image model of the Retina for fundus image understanding.

  Language:Python75257

• jiayi-ma/DDcGAN

  DDcGAN: A Dual-discriminator Conditional Generative Adversarial Network for Multi-resolution Image Fusion / Learning a Generative Model for Fusing Infrared and Visible Images via Conditional Generative Adversarial Network with Dual Discriminators

  Language:Python49109

• dhh1995/SCL

  PyTorch implementation for The Scattering Compositional Learner (SCL)

  Language:Python33354

• compdemocracy/openData

  :open_file_folder: Data exports from select "open data" Polis conversations

  26328

• serre-lab/CVR

  A Benchmark for Efficient and Compositional Visual Reasoning

  Language:Python17216

• dapello/braintree

  Language:Jupyter Notebook8312

• Spandan-Madan/in_distribution_adversarial_examples

  Source code for the paper: "Adversarial examples within the training distribution: A widespread challenge"

  Language:Jupyter Notebook6301

• MorganBDT/crumb

  Compositional Replay Using Memory Blocks (CRUMB) is a replay algorithm for online stream learning that stores and replays training examples at a feature level using a differentiable codebook to mitigate catastrophic forgetting. This repo also contains instructions for setting up the Toybox and iLab-2M-Light stream learning benchmarks.

  Language:Python1