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Starred repositories
For an education purpose, from-scratch, single-file, python-only pose-graph optimization implementation
Source code and data for papers "Improved Scene Landmark Detection for Camera Localization" (3DV 2024) and "Learning to Detect Scene Landmarks for Camera Localization" (CVPR 2024).
《Hello 算法》:动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新,English version ongoing
【A common used C++ DAG framework】 一个通用的、无三方依赖的、跨平台的、收录于awesome-cpp的、基于流图的并行计算框架。欢迎star & fork & 交流
LiteVLoc: Map-Lite Visual Localization for Image Goal Navigation
3DGS-LM accelerates Gaussian-Splatting optimization by replacing the ADAM optimizer with Levenberg-Marquardt.
SplatLoc: 3D Gaussian Splatting-based Visual Localization for Augmented Reality
[CVPR'24] LEAP-VO: Long-term Effective Any Point Tracking for Visual Odometry
LetsGo: Large-Scale Garage Modeling and Rendering via LiDAR-Assisted Gaussian(Published in SIGGRAPH Asia 2024)
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
CoTracker is a model for tracking any point (pixel) on a video.
[NeurIPS'24] NeuRodin: A Two-stage Framework for High-Fidelity Neural Surface Reconstruction
A python tool for fitting primitives 3D shapes in point clouds using RANSAC algorithm
VGGSfM: Visual Geometry Grounded Deep Structure From Motion
[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation
From anything to mesh like human artists. Official impl. of "MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformers"
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
[CVPR 2024 Highlight] Map-Relative Pose Regression for Visual Re-Localization
Source Code for Paper "OrienterNet Visual Localization in 2D Public Maps with Neural Matching"
nanoflann: a C++11 header-only library for Nearest Neighbor (NN) search with KD-trees
C++ libraries and programs demonstrating mesh processing research published in ACM SIGGRAPH (1992-2003)