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a generalist algorithm for cellular segmentation with human-in-the-loop capabilities

From cell instance segmentation to Tree crown instance segmentation

The uncompromising Python code formatter

A collaboration friendly studio for NeRFs

A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷

LightGlue: Local Feature Matching at Light Speed (ICCV 2023)

Efficient neural feature detector and descriptor

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

Roadmap to become a Visual-SLAM developer in 2026

📍PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency [TRO 24]

COLMAP - Structure-from-Motion and Multi-View Stereo

VGGSfM: Visual Geometry Grounded Deep Structure From Motion

Highly recommended resources for SLAM newbies (Lecture, Reviewed paper, Books, Tutorial, etc)

2026 科学上网/魔法上网教程：Clash 机场 + VPN + VPS 图文指南，持续更新，从 0 到 1 带你突破网络封锁

[CVPR 2025 Oral] SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image …

Code for RSAM-Seg

🛣 Building an end-to-end Promptable Semantic Segmentation (Computer Vision) project from training to inferencing a model on LandCover.ai data (Satellite Imagery).

NASA ABoVE 10m Composite DEM scripts and codes

Source code of the TLSeparation Python package.

Code for the paper "TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds"

PyCrown - Fast raster-based individual tree segmentation for LiDAR data

Extract individual trees from lidar point clouds

Python package for automatic tree crown delineation based on the Detectron2 implementation of Mask R-CNN

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

official source code for paper entitled "Automated forest inventory: analysis of high-density airborne LiDAR point clouds with 3D deep learning"

A deep learning model for segmenting trees from RGB images