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d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被55个国家的300所大学用于教学。

deep-learning-for-image-processing

deep learning for image processing including classification and object-detection etc.

dive_into_deep_learning

✔️李沐 【动手学深度学习】课程学习笔记：使用pycharm编程，基于pytorch框架实现。

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

generalized_contrastive_loss

google-landmark

Dataset with 5 million images depicting human-made and natural landmarks spanning 200 thousand classes.

heaputil

Code for the RA-L (IROS) 2021 paper "A Hierarchical Dual Model of Environment- and Place-Specific Utility for Visual Place Recognition"

hierarchical-localization

Visual localization made easy with hloc

iccv2021-paper-code-interpretation

ICCV2021/2019/2017 论文/代码/解读/直播合集，极市团队整理

image

images

kapture-localization

Provide mapping and localization pipelines based on kapture format

patch-netvlad

Code for the CVPR2021 paper "Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition"

pycolmap

Python bindings for COLMAP

pyseqslam

Python SeqSLAM - port of Niko Sünderhauf's OpenSeqSLAM for place recognition

pytorch-netvlad

Pytorch implementation of NetVlad including training on Pittsburgh.

seqnet

SeqNet: Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"

spatio-temporal-seqvpr

Learning Sequence Descriptor based on Spatio-Temporal Attention for Visual Place Recognition

superglue-pytorch

[SuperGlue: Learning Feature Matching with Graph Neural Networks] This repo includes PyTorch code for training the SuperGlue matching network on top of SIFT keypoints and descriptors.

vins-mono-learning

VINS-Mono代码注释，仅供学习

vision_transformer

vit-pytorch

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

vpr-datasets-downloader

Automatic download VPR datasets in a standard format