Songchunzhang's repositories

project-based-learning

Curated list of project-based tutorials

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gaussian-opacity-fields

Gaussian Opacity Fields for Efficient and Compact Surface Reconstruction in Unbounded Scenes

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GaussianSplats3D

Three.js-based implementation of 3D Gaussian splatting

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video2game

Code release of Video2Game

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svd-mv

Training code for Stable Video Diffusion Multi-View

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gaussian-splatting-mini

A minimize training version of 3DGS

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DiffSF

Official repository for paper: DiffSF: Diffusion Models for Scene Flow Estimation

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QAnything

Question and Answer based on Anything.

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Dynamo-Depth

[NeurIPS 2023] Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes

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RecSysPapers

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

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genvs_unofficial

Unofficial (partial) reimplementation of GeNVS by Chan et al.

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SDfu

Stable Diffusers for studies

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tmpl

⚡ A template for rapid & flexible DL experimentation development, built upon Lightning & Hydra with best practice.

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PythonRobotics

Python sample codes for robotics algorithms.

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cs-self-learning

计算机自学指南

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learning_research

本人博士期间的科研经验

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trt-samples-for-hackathon-cn

Simple samples for TensorRT programming

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CPlusPlusThings

C++那些事

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ACMMM2023Workshop

ACM MM2023 Workshop on UAVs in Multimedia: Capturing the World from a New Perspective

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DIM-SLAM

This is official repo for ICLR 2023 Paper "DENSE RGB SLAM WITH NEURAL IMPLICIT MAPS"

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lightning-hydra-template

PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡

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OpenOcc

Open Source 3D Occupancy Prediction Library.

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torch-ngp

A pytorch CUDA extension implementation of instant-ngp (sdf and nerf), with a GUI.

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Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models

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VFDepth

VFDepth Self-supervised surround-view depth estimation with volumetric feature fusion

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Awesome-monocular-3d-object-detection

Image based 3d object detection paper list

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ENeRF

Real-time novel view synthesis for dynamic scenes.

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