colin-de Goto Github PK

airdos

This work is a dynamic object slam work

automatic-wheel-assembly-detection

Technical University of Denmark (02476)

autonomous_uav_ros_unity

This code is a project from "Autonomous Systems" taught at the Technical University of Munich.

awesome-implicit-nerf-slam

A comprehensive list of Implicit Representations and NeRF papers relating to SLAM/Robotics domain, including papers, video, codes, and related websites

chatgpt_academic

科研工作专用ChatGPT拓展，特别优化学术Paper润色体验，支持自定义快捷按钮，支持自定义函数插件，支持markdown代码块表格显示，Tex公式双显示，新增Python/C++项目剖析/自译解功能，PDF/LaTex论文翻译/总结功能，兼容ChatGLM等本地模型

cpp-nano-udacity

This is my projects in the Cpp Nano Degree offered by Udacity

deep-linear-shapes

PyTorch implementation of "Representing Shape Collections with Alignment-Aware Linear Models" paper.

dtu_mlops

Exercises and supplementary material for the machine learning operations course at DTU.

employee-management-system

Employee management system can be used to manage all the information of employees in the company

ethz-duckietown-mooc-exercises

fastsam

Fast Segment Anything

gaussian-splatting

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

grounded-segment-anything

Grounded-SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

hndr

Official code repository for the paper: "The Implicit Values of A Good Hand Shake: Handheld Multi-Frame Neural Depth Refinement"

linear-algebra-python-matlab

lod3_buildings

This repository contains the codes for computing geometrical digital twins as LOD3 models for buildings using a structure from motion and semantic segmentation. The methodoly hereby implementes was presented in the paper "Generating LOD3 building models from structure-from-motion and semantic segmentation" by Pantoja-Rosero et., al.

my_mlops

nerfstudio

A collaboration friendly studio for NeRFs

nice-slam

[CVPR'22] NICE-SLAM: Neural Implicit Scalable Encoding for SLAM

nope-nerf

(CVPR 2023) NoPe-NeRF: Optimising Neural Radiance Field with No Pose Prior

orb_slam2

Real-Time SLAM for Monocular, Stereo and RGB-D Cameras, with Loop Detection and Relocalization Capabilities

orb_slam3

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

orbslam2_with_pointcloud_map

pyceres

Factor graphs with Ceres in Python

pypose

A library for differentiable robotics.

python-notes

My notes about basic concepts of python, pyqt and pygame

pytorch-cppcuda-tutorial

tutorial for writing custom pytorch cpp+cuda kernel, applied on volume rendering (NeRF)

ros-theory-application

rossmann-store-sales-forecast

# Forecast Rossmann's future sales Rossmann is Germany's largest supermarket for daily necessities and was founded in 1972. In the pharmaceutical retail sector, Rossmann now has more than 3,000 pharmacies in seven European countries. Currently, Rossmann store managers have the task of **forecasting their daily sales** six weeks in advance. Obviously, store sales are influenced by many factors, such as promotions, competition, holidays, seasonality and location, to name a few. Thousands of individual managers forecast sales based on their individual stores, and the accuracy of the results can vary greatly. Reliable sales forecasting enables store managers to create effective staff schedules that increase productivity and motivation, such as better alignment of supply chains and sound promotional and competitive strategies, with significant practical and strategic value. If Rossmann can be helped to create a powerful forecasting model, it will help warehouse managers to focus on what is most important to them: their customers and their teams. Therefore, in this project, Rossmann wanted to build machine learning models to predict 6 weeks of sales for 1115 stores across Germany with the given data.

sdfstudio

A Unified Framework for Surface Reconstruction