Stars
Python package for Korean natural language processing.
CoreNet: A library for training deep neural networks
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Paper bank of visual / universal / general foundation models
General Vision Benchmark, GV-B, a project from OpenGVLab
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation
Official pytorch implementation of Rainbow Memory (CVPR 2021)
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning, CVPR 2021
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Fast Near-Duplicate Image Search and Delete using pHash, t-SNE and KDTree.
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Multi-Label Siamese Attention Network for Chest X-ray Screening
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
Implementation of Optimal Transport-driven CycleGAN (OT-CycleGAN)
Implementation of Non-local Block.
Standardizing weights to accelerate micro-batch training
Regularizing Class-wise Predictions via Self-knowledge Distillation (CVPR 2020)
The hub of pre-trained models in the medical domain
What I have read papers about deep learning