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Image to 3D
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/yisuanwang/idea23d
공식 코드Idea23D: Collaborative LMM Agents Enable 3D Model Generation from Interleaved Multimodal Inputs
https://github.com/yuqiao0303/fancy123
공식 코드Fancy123: One Image to High-Quality 3D Mesh Generation via Plug-and-Play Deformation
https://github.com/yxymessi/dtc123
공식 코드Diffusion Time-step Curriculum for One Image to 3D Generation
https://github.com/zengbohan0217/ipdreamer
공식 코드IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
https://github.com/zhaorw02/FlexiDreamer
공식 코드https://github.com/ziangcao0312/PhysX
공식 코드https://huggingface.co/datasets/sankalpsinha77/MARVEL-40M
공식 코드MARVEL-40M+: Multi-Level Visual Elaboration for High-Fidelity Text-to-3D Content Creation
https://github.com/3dtopia/openlrm
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/chenguolin/DiffSplat
SV3D: Novel Multi-view Synthesis and 3D Generation from a Single Image using Latent Video Diffusion
https://github.com/gchb2012/VQA
Let's Transfer Transformations of Shared Semantic Representations
https://github.com/lugiavn/transformation-transferring
Let's Transfer Transformations of Shared Semantic Representations
https://github.com/megvii-research/conr
https://github.com/megvii-research/ijcai2023-conr
https://github.com/nsarafianos/Garment3DGen
https://github.com/sap3d/Sap3D
https://github.com/transpchan/Live3D-v2
https://github.com/wu-cvgl/mvcontrol
Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting
https://github.com/xxlong0/wonder3d
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.