jiangzt's repositories
3DFuse
Official implementation of "Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation"
amazon-sagemaker-codeserver
Hosting code-server on Amazon SageMaker
awesome-3D-generation
A curated list of awesome 3d generation papers
Awesome-AIGC-3D
A curated list of awesome AIGC 3D papers
ChatGPT
Reverse engineered ChatGPT API
ChatPaper
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文总结+润色+审稿+审稿回复
clip-interrogator
Image to prompt with BLIP and CLIP
daam
Diffusion attentive attribution maps for interpreting Stable Diffusion.
Fantasia3D
official repository for "Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation"
LAVIS
LAVIS - A One-stop Library for Language-Vision Intelligence
llama-dl
High-speed download of LLaMA, Facebook's 65B parameter GPT model
LLaVA
[NeurIPS 2023 Oral] Visual Instruction Tuning: LLaVA (Large Language-and-Vision Assistant) built towards multimodal GPT-4 level capabilities.
LRV-Instruction
Aligning Large Multi-Modal Model with Robust Instruction Tuning
MiniGPT-4
Open-sourced codes for MiniGPT-4 and MiniGPT-v2
mmgeneration
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.
NeRFs-CVPR2023
All NeRF-related papers on CVPR2023
nerfstudio
A collaboration friendly studio for NeRFs
NFD
Official codebase for the paper "3D Neural Field Generation using Triplane Diffusion"
point-e
Point cloud diffusion for 3D model synthesis
recognize-anything
Code for the Recognize Anything Model (RAM) and Tag2Text Model
sdfstudio
A Unified Framework for Surface Reconstruction
seamless_communication
Foundational Models for State-of-the-Art Speech and Text Translation
stable-dreamfusion
A pytorch implementation of text-to-3D dreamfusion, powered by stable diffusion.
stablediffusion
High-Resolution Image Synthesis with Latent Diffusion Models
threestudio
A unified framework for 3D content generation.
X-Dreamer
A pytorch implementation of “X-Dreamer: Creating High-quality 3D Content by Bridging the Domain Gap Between Text-to-2D and Text-to-3D Generation”
zero123
Zero-1-to-3: Zero-shot One Image to 3D Object: https://zero123.cs.columbia.edu/