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  • 👋 Hi, I’m @QinZiwen
  • 👀 I’m interested in V-SLAM, SFM, deeplearning
  • 🌱 I’m currently learning VIO
  • 💞️ I’m looking to collaborate on V-SLAM
  • 📫 [email protected]

lion's Projects

pytorch-metric-learning icon pytorch-metric-learning

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

recent-stars-2020 icon recent-stars-2020

:star: SLAM, Pose/Object tracking, Depth/Disparity/Flow Estimation, 3D-graphic, etc. related papers and code

reslam icon reslam

RESLAM: A real-time robust edge-based SLAM system

revo icon revo

Robust Edge-based Visual Odometry (REVO)

rpmnet icon rpmnet

RPM-Net: Robust Point Matching using Learned Features (CVPR2020)

rtabmap icon rtabmap

RTAB-Map library and standalone application

simvodis icon simvodis

Simultaneous Visual Odometry, Object Detection, and Instance Segmentation

sit icon sit

Self-supervised vIsion Transformer (SiT)

slam-all-in-one icon slam-all-in-one

SLAM汇总,包括多传感器融合建图、定位、VIO系列、常用工具包、开源代码注释和公式推导、文章综述

sold2 icon sold2

Joint deep network for feature line detection and description

sphericalviewsynthesis icon sphericalviewsynthesis

Code accompanying the paper "Spherical View Synthesis for Self-Supervised 360 Depth Estimation", 3DV 2019

stba icon stba

Stochastic Bundle Adjustment for Efficient and Scalable Structure from Motion (ECCV 2020)

stvo-pl icon stvo-pl

Stereo Visual Odometry by combining point and line segment features

theiasfm icon theiasfm

An open source library for multiview geometry and structure from motion

tinyxml2 icon tinyxml2

TinyXML2 is a simple, small, efficient, C++ XML parser that can be easily integrated into other programs.

transformer-explainability icon transformer-explainability

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

triplet-attention icon triplet-attention

Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]

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