3DGen-Arena / model /model_registry.py
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add InstantMesh
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from collections import namedtuple
from typing import List
ModelInfo = namedtuple("ModelInfo", ["simple_name", "link", "description"])
model_info = {}
def register_model_info(
full_names: List[str], simple_name: str, link: str, description: str
):
info = ModelInfo(simple_name, link, description)
for full_name in full_names:
model_info[full_name] = info
def get_model_info(name: str) -> ModelInfo:
if name in model_info:
return model_info[name]
else:
# To fix this, please use `register_model_info` to register your model
return ModelInfo(
name, "", "Register the description at fastchat/model/model_registry.py"
)
def get_model_description_md(model_list):
model_description_md = """
| | | |
| ---- | ---- | ---- |
"""
ct = 0
visited = set()
for i, name in enumerate(model_list):
minfo = get_model_info(name)
if minfo.simple_name in visited:
continue
visited.add(minfo.simple_name)
one_model_md = f"[{minfo.simple_name}]({minfo.link}): {minfo.description}"
if ct % 3 == 0:
model_description_md += "|"
model_description_md += f" {one_model_md} |"
if ct % 3 == 2:
model_description_md += "\n"
ct += 1
return model_description_md
# regist text-to-shape generation models
register_model_info(
["dreamfusion"],
"DreamFusion",
"https://dreamfusion3d.github.io/",
"Text-to-3D using 2D Diffusion and SDS Loss",
)
register_model_info(
["fantasia3d"],
"Fantasia3D",
"https://fantasia3d.github.io/",
"Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation",
)
register_model_info(
["instant3d"],
"Instant3D",
"https://jiahao.ai/instant3d/",
"Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model",
)
register_model_info(
["latent-nerf"],
"Latent-NeRF",
"https://github.com/eladrich/latent-nerf",
"Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures",
)
register_model_info(
["magic3d"],
"Magic3D",
"https://research.nvidia.com/labs/dir/magic3d/",
"High-Resolution Text-to-3D Content Creation",
)
register_model_info(
["geodream"],
"GeoDream",
"https://mabaorui.github.io/GeoDream_page/",
"Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation",
)
register_model_info(
["lucid-dreamer"],
"LucidDreamer",
"https://github.com/EnVision-Research/LucidDreamer",
"Towards High-Fidelity Text-to-3D Generation via Interval Score Matching",
)
register_model_info(
["mvdream"],
"MVDream",
"https://github.com/bytedance/MVDream",
"Multi-view Diffusion for 3D Generation",
)
register_model_info(
["grm-t", "grm-i"],
"GRM",
"https://justimyhxu.github.io/projects/grm",
"GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation",
)
register_model_info(
["point-e-t", "point-e-i"],
"Point·E",
"https://github.com/openai/point-e",
"A System for Generating 3D Point Clouds from Complex Prompts",
)
register_model_info(
["shap-e-t", "shap-e-i"],
"Shap-E",
"https://github.com/openai/shap-e",
"Generating Conditional 3D Implicit Functions",
)
register_model_info(
["prolificdreamer"],
"ProlificDreamer",
"https://ml.cs.tsinghua.edu.cn/prolificdreamer/",
"High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation",
)
register_model_info(
["sjc"],
"Score Jacobian Chaining",
"https://pals.ttic.edu/p/score-jacobian-chaining",
"Lifting Pretrained 2D Diffusion Models for 3D Generation",
)
# register_model_info(
# [],
# "",
# "",
# "",
# )
## regist image-to-shape generation models
register_model_info(
["dreamgaussian"],
"DreamGaussian",
"https://github.com/dreamgaussian/dreamgaussian",
"Generative Gaussian Splatting for Efficient 3D Content Creation",
)
register_model_info(
["wonder3d"],
"Wonder3D",
"https://github.com/xxlong0/Wonder3D",
"Single Image to 3D using Cross-Domain Diffusion",
)
register_model_info(
["dreamcraft3d"],
"Dreamcraft3d",
"https://github.com/deepseek-ai/DreamCraft3D",
"Hierarchical 3d generation with bootstrapped diffusion prior",
)
register_model_info(
["syncdreamer"],
"SyncDreamer",
"https://github.com/liuyuan-pal/SyncDreamer",
"Generating Multiview-consistent Images from a Single-view Image",
)
register_model_info(
["zero123"],
"Zero-1-to-3",
"https://github.com/cvlab-columbia/zero123",
"Zero-shot One Image to 3D Object",
)
register_model_info(
["stable-zero123"],
"Stable Zero123",
"https://stability.ai/news/stable-zero123-3d-generation",
"Quality 3D Object Generation from Single Images",
)
register_model_info(
["zero123-xl"],
"Zero123-XL",
"https://stability.ai/news/stable-zero123-3d-generation",
"Quality 3D Object Generation from Single Images",
)
register_model_info(
["magic123"],
"Magic123",
"https://guochengqian.github.io/project/magic123/",
"One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors",
)
register_model_info(
["imagedream"],
"ImageDream",
"https://github.com/bytedance/ImageDream",
"Image-Prompt Multi-view Diffusion for 3D Generation",
)
register_model_info(
["make-it-3d"],
"Make-It-3D",
"https://github.com/junshutang/Make-It-3D",
"High-Fidelity 3D Creation from A Single Image with Diffusion Prior",
)
register_model_info(
["triplane-gaussian"],
"TriplaneGaussian",
"https://github.com/VAST-AI-Research/TriplaneGaussian",
"Triplane Meets Gaussian Splatting: Fast and Generalizable Single-View 3D Reconstruction with Transformers",
)
register_model_info(
["free3d"],
"Free3D",
"https://github.com/lyndonzheng/Free3D",
"Consistent Novel View Synthesis without 3D Representation",
)
register_model_info(
["escher-net"],
"EscherNet",
"https://github.com/kxhit/EscherNet",
"A Generative Model for Scalable View Synthesis",
)
register_model_info(
["v3d"],
"V3D",
"https://github.com/heheyas/V3D",
"Video Diffusion Models are Effective 3D Generators",
)
register_model_info(
["lgm"],
"LGM",
"https://github.com/3DTopia/LGM",
"Large Multi-View Gaussian Model for High-Resolution 3D Content Creation",
)
register_model_info(
["gsgen"],
"GSGEN",
"https://github.com/gsgen3d/gsgen",
"Text-to-3D using Gaussian Splatting",
)
register_model_info(
["openlrm"],
"OpenLRM",
"https://github.com/3DTopia/OpenLRM",
"Open-Source Large Reconstruction Models",
)
register_model_info(
["hifa"],
"HiFA",
"https://github.com/JunzheJosephZhu/HiFA",
"High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance",
)
register_model_info(
["instant-mesh"],
"InstantMesh",
"https://github.com/TencentARC/InstantMesh",
"Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models",
)
# register_model_info(
# [],
# "",
# "",
# "",
# )