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3D Generation

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/wyysf-98/craftsman3d

공식 코드

CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner

https://github.com/xingy038/dreamer-xl

공식 코드

Dreamer XL: Towards High-Resolution Text-to-3D Generation via Trajectory Score Matching

https://github.com/xmu-xiaoma666/X-Dreamer

공식 코드

X-Dreamer: Creating High-quality 3D Content by Bridging the Domain Gap Between Text-to-2D and Text-to-3D Generation

https://github.com/yanghb22-fdu/hi3d-official

공식 코드

Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Models

https://github.com/yangxiaofeng/rectified_flow_prior

공식 코드

Text-to-Image Rectified Flow as Plug-and-Play Priors

https://github.com/yanllan-ljb/contrastivegaussian

공식 코드

ContrastiveGaussian: High-Fidelity 3D Generation with Contrastive Learning and Gaussian Splatting

https://github.com/yhyang-myron/sampart3d-website

공식 코드

SAMPart3D: Segment Any Part in 3D Objects

https://github.com/yikaiw/vidu4d

공식 코드

Video4DGen: Enhancing Video and 4D Generation through Mutual Optimization

https://github.com/yisuanwang/idea23d

공식 코드

Idea23D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs

https://github.com/yjhboy/hyper3dg

공식 코드

Hyper-3DG: Text-to-3D Gaussian Generation via Hypergraph

https://github.com/yxymessi/dtc123

공식 코드

Diffusion Time-step Curriculum for One Image to 3D Generation

https://github.com/zengbohan0217/ipdreamer

공식 코드

IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts

https://github.com/zhaorw02/FlexiDreamer

공식 코드

FlexiDreamer: Single Image-to-3D Generation with FlexiCubes

https://github.com/zhengxinyang/sdf-stylegan

공식 코드

SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation

https://github.com/ziangcao0312/DiffTF

공식 코드

DiffTF++: 3D-aware Diffusion Transformer for Large-Vocabulary 3D Generation

https://github.com/ziangcao0312/PhysX

공식 코드

PhysX: Physical-Grounded 3D Asset Generation

https://github.com/ziyuguo99/point-bind_point-llm

공식 코드

Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following

https://github.com/zyj-2000/3dgcqa

공식 코드

3DGCQA: A Quality Assessment Database for 3D AI-Generated Contents

https://github.com/zymvszym/ExactDreamer

공식 코드

ExactDreamer: High-Fidelity Text-to-3D Content Creation via Exact Score Matching

https://github.com/DreamTechAI/Direct3D

Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer

https://github.com/DreamTechAI/Direct3D-S2

Direct3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention

https://github.com/MS-Mind/MS-Code-04

LION: Latent Point Diffusion Models for 3D Shape Generation

https://github.com/MindCode-4/code-10/tree/main/MVD

MVDream: Multi-view Diffusion for 3D Generation

https://github.com/Pointcept/GPT4Point

Point-Bind & Point-LLM: Aligning Point Cloud with Multi-modality for 3D Understanding, Generation, and Instruction Following

https://github.com/Seed3D/Dora

CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner

https://github.com/bytedance/MVDream-threestudio

MVDream: Multi-view Diffusion for 3D Generation

https://github.com/bytedance/imagedream

ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation

https://github.com/bytedance/mvdream

MVDream: Multi-view Diffusion for 3D Generation

https://github.com/chenguolin/DiffSplat

SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusion

https://github.com/chenguolin/InstructScene

NAP: Neural 3D Articulation Prior

https://github.com/cvlab-columbia/zero123

NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priors

https://github.com/cyjdlhy/DreamInit

A General Framework to Boost 3D GS Initialization for Text-to-3D Generation by Lexical Richness

https://github.com/drexubery/viewcrafter

ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesis

https://github.com/gnobitab/instaflow

Text-to-Image Rectified Flow as Plug-and-Play Priors

https://github.com/huanngzh/MV-Adapter

MV-Adapter: Multi-view Consistent Image Generation Made Easy

https://github.com/icoz69/stablellava

StyleAvatar3D: Leveraging Image-Text Diffusion Models for High-Fidelity 3D Avatar Generation

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