ywyue Goto Github PK

3d-machine-learning

A resource repository for 3D machine learning

568-final-project

Final Project for EECS/NAVARCH 568 (Mobile Robotics)

academicpages

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

adelaidet

AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.

agile3d

[ICLR 2024] AGILE3D: Attention Guided Interactive Multi-object 3D Segmentation

ar_lbsfitness

asis

Associatively Segmenting Instances and Semantics in Point Clouds, CVPR 2019

awesome-geospatial

Long list of geospatial tools and resources

awesome-llm-3d

Awesome-LLM-3D: a curated list of Multi-modal Large Language Model in 3D world Resources

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome-point-cloud-analysis

A list of papers and datasets about point cloud analysis (processing)

awesome-transformer-attention

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

bmp_processor

Coursework for [Map Algebra](2018fall)

books-sales-management-software

An open source book sales management software written by Java.

convpoint

covid-trade

Web storymap project in Cartography Lab at ETH Zurich.

detr

End-to-End Object Detection with Transformers

diffusiondet

PyTorch implementation of DiffusionDet (https://arxiv.org/abs/2211.09788)

evo

Python package for the evaluation of odometry and SLAM

first-contributions

🚀✨ Help beginners to contribute to open source projects

geoar.js

A lightweight library for Web Location-based Augmented Reality.

heat

Code for "HEAT: Holistic Edge Attention Transformer for Structured Reconstruction", CVPR 2022

ici-backend

ici-v2-ios

ici-here/version2/ios

image-to-image-translation-a-literature-review

Documents for ETH Geomatics Seminar HS20

implicity

ImpliCity: City Modeling from Satellite Images with Deep Implicit Occupancy Fields

lane-marking-detection

This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.

lanemapper

laser-slam-study

Laser slam - from theory to practice

ldrt

Virtual Lane Boundary Generation for Human-Compatible Autonomous Driving