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Druid Ting's Projects

meshdiffusion icon meshdiffusion

Official implementation of "MeshDiffusion: Score-based Generative 3D Mesh Modeling" (ICLR 2023 Spotlight)

meshroom2blender icon meshroom2blender

Blender importer of meshroom datafiles: cameras, images, sparse pointcloud and obj's.

mirror icon mirror

#1 Open Source Unity Networking Library

mixer icon mixer

Add-on for real-time collaboration in Blender.

ml-agents icon ml-agents

The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.

nlp-tutorials icon nlp-tutorials

Simple implementations of NLP models. Tutorials are written in Chinese on my website https://mofanpy.com

open3d icon open3d

Open3D: A Modern Library for 3D Data Processing

opencv icon opencv

Open Source Computer Vision Library

openlrm icon openlrm

An open-source impl. of Large Reconstruction Models

openrpa icon openrpa

Free Open Source Enterprise Grade RPA

pallaidium icon pallaidium

Text, video or image to video, image and audio in Blender Video Sequence Editor using Zeroscope (SD, XL, upscale to XL), Animov, Potat1, Stable Diffusion(1.5, 2.0, XL), Deep Floyd IF, AudioLDM2 and Bark.

pifu icon pifu

This repository contains the code for the paper "PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization"

pifuhd icon pifuhd

High-Resolution 3D Human Digitization from A Single Image.

point-e icon point-e

Point cloud diffusion for 3D model synthesis

posepipe icon posepipe

Blender Python - Camera Motion Capture using OpenCV and Mediapipe

pytorch3d icon pytorch3d

PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

real-esrgan icon real-esrgan

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

robotics-object-pose-estimation icon robotics-object-pose-estimation

A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

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