Merrical

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

CVPR2024-Paper-Code-Interpretation

cvpr2024/cvpr2023/cvpr2022/cvpr2021/cvpr2020/cvpr2019/cvpr2018/cvpr2017 论文/代码/解读/直播合集，极市团队整理

tutorials

PyTorch tutorials.

PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

Deformable-DETR

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

CV-Surveys

计算机视觉相关综述。包括目标检测、跟踪........

Federated-Learning-PyTorch

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

batchgenerators

A framework for data augmentation for 2D and 3D image classification and segmentation

probabilistic_unet

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

hamiltorch

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks

Probabilistic-Unet-Pytorch

A Probabilistic U-Net for segmentation of ambiguous images implemented in PyTorch

FedBN

[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

PiCO

PyTorch implementation of PiCO https://arxiv.org/abs/2201.08984

cifar-10-100n

Human annotated noisy labels for CIFAR-10 and CIFAR-100. The website of CIFAR-N is available at http://www.noisylabels.com/.

VPT

Unofficial code for VPT(Visual Prompt Tuning) paper of arxiv 2203.12119

PENCIL

PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.

negative-label-smoothing

[ICML2022 Long Talk] Official Pytorch implementation of "To Smooth or Not? When Label Smoothing Meets Noisy Labels"

ALFs

Learning with Noisy Labels, Label Noise, ICML 2021

CARSSS

Official re-implementation of the Calibrated Adversarial Refinement model described in the paper "Calibrated Adversarial Refinement for Stochastic Semantic Segmentation"

Taming-VAEs

SPR-LNL

This is the official repo for our CVPR22 paper: Scalable Penalized Regression for Noise Detection in Learning With Noisy Labels.

SVLS

MEIDTM-Instance-Dependent-Label-Noise-Learning-with-Manifold-Regularized-Transition-Matrix-Estimatio

pytorch