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Hi there 👋

I'm a Ph.D. student focusing on camera pose estimation, mapping, and scene understanding at Technical University of München.

My future research interests are SLAM for different sensors, NeRF-SLAM and reinforcement learning.

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Yanyan Li's Projects

a_survey_of_slam icon a_survey_of_slam

The source file of paper in Latex and frame in Visio and XMind (A Survey of Simultaneous Localization and Mapping)

compgcn icon compgcn

ICLR 2020: Composition-Based Multi-Relational Graph Convolutional Networks

evaluatetools icon evaluatetools

This repo provides useful tools for evaluating SLAM systems

geogaussian icon geogaussian

GeoGaussian: Geometry-aware Gaussian Splatting for Scene Rendering

normal_depth_gt_of_nyu2 icon normal_depth_gt_of_nyu2

A simple image generator for NYU2 (labeled dataset), which provides independent images for your evaluation goals.

open-structure icon open-structure

This new benchmark dataset, Open-Structure, is proposed to evaluate visual odometry and SLAM methods, which directly equips point and line measurements, correspondences, structural associations, and co-visibility factor graphs instead of providing raw images.

orb_slam3 icon orb_slam3

ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM

peac icon peac

Fast Plane Extraction Using Agglomerative Hierarchical Clustering (AHC)

pl-vio icon pl-vio

monocular visual inertial system with point and line features

planarslam icon planarslam

A RGB-D SLAM system for structural scenes, which makes use of point-line-plane features and the Manhattan World assumption.

planematch icon planematch

[ECCV'18 Oral] PlaneMatch: Patch Coplanarity Prediction for Robust RGB-D Reconstruction

planenet icon planenet

PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image

potree icon potree

WebGL point cloud viewer for large datasets

slam-book icon slam-book

这是一本关于SLAM的书稿,希望能清楚的介绍SLAM系统中的使用的几何方法和深度学习方法。书稿最后应该会达到200页左右,书稿每章对应的代码也会被整理出来。

venom-slam icon venom-slam

This is a simulator software for SLAM. The pose estimation strategy, Venom, receives enhanced powers when structure primities are deteced from environments.

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