✨LEGO-Eval: Towards Fine-Grained Evaluation on Synthesizing 3D Embodied Environments with Tool Augmentation
📝 Summary:
The paper introduces LEGO-Eval, a tool-augmented framework, and LEGO-Bench, a detailed instruction benchmark, to improve 3D scene evaluation. It shows LEGO-Eval accurately assesses scene-instruction alignment, outperforming VLMs, and current generation methods largely fail to create realistic sce...
🔹 Publication Date: Published on Nov 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03001
• PDF: https://arxiv.org/pdf/2511.03001
• Project Page: https://gyeomh.github.io/LEGO-Eval/
==================================
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#EmbodiedAI #3DGeneration #EvaluationMetrics #VLMs #Benchmarking
📝 Summary:
The paper introduces LEGO-Eval, a tool-augmented framework, and LEGO-Bench, a detailed instruction benchmark, to improve 3D scene evaluation. It shows LEGO-Eval accurately assesses scene-instruction alignment, outperforming VLMs, and current generation methods largely fail to create realistic sce...
🔹 Publication Date: Published on Nov 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.03001
• PDF: https://arxiv.org/pdf/2511.03001
• Project Page: https://gyeomh.github.io/LEGO-Eval/
==================================
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#EmbodiedAI #3DGeneration #EvaluationMetrics #VLMs #Benchmarking
✨WorldGen: From Text to Traversable and Interactive 3D Worlds
📝 Summary:
WorldGen transforms text prompts into interactive 3D worlds. It combines LLM reasoning with procedural and diffusion-based 3D generation to efficiently create coherent, navigable environments for gaming and simulation.
🔹 Publication Date: Published on Nov 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.16825
• PDF: https://arxiv.org/pdf/2511.16825
• Project Page: https://www.meta.com/blog/worldgen-3d-world-generation-reality-labs-generative-ai-research/
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#3DGeneration #GenerativeAI #LLMs #VirtualWorlds #AIResearch
📝 Summary:
WorldGen transforms text prompts into interactive 3D worlds. It combines LLM reasoning with procedural and diffusion-based 3D generation to efficiently create coherent, navigable environments for gaming and simulation.
🔹 Publication Date: Published on Nov 20
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.16825
• PDF: https://arxiv.org/pdf/2511.16825
• Project Page: https://www.meta.com/blog/worldgen-3d-world-generation-reality-labs-generative-ai-research/
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✨SyncMV4D: Synchronized Multi-view Joint Diffusion of Appearance and Motion for Hand-Object Interaction Synthesis
📝 Summary:
SyncMV4D generates realistic and consistent multi-view 3D Hand-Object Interaction videos and 4D motions. It unifies visual priors, motion dynamics, and multi-view geometry, using a joint diffusion model and a point aligner for robust generation.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19319
• PDF: https://arxiv.org/pdf/2511.19319
• Project Page: https://droliven.github.io/SyncMV4D/
• Github: https://droliven.github.io/SyncMV4D/
==================================
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#HandObjectInteraction #DiffusionModels #3DGeneration #ComputerVision #GenerativeAI
📝 Summary:
SyncMV4D generates realistic and consistent multi-view 3D Hand-Object Interaction videos and 4D motions. It unifies visual priors, motion dynamics, and multi-view geometry, using a joint diffusion model and a point aligner for robust generation.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.19319
• PDF: https://arxiv.org/pdf/2511.19319
• Project Page: https://droliven.github.io/SyncMV4D/
• Github: https://droliven.github.io/SyncMV4D/
==================================
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✨Yo'City: Personalized and Boundless 3D Realistic City Scene Generation via Self-Critic Expansion
📝 Summary:
Yo'City is an agentic framework for personalized, infinitely expandable 3D city scene generation. It leverages large models with hierarchical planning, a self-critic image synthesis loop, and relationship-guided expansion for spatially coherent growth. Yo'City outperforms existing methods.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.18734
• PDF: https://arxiv.org/pdf/2511.18734
==================================
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#3DGeneration #GenerativeAI #CityGeneration #ProceduralGeneration #ComputerGraphics
📝 Summary:
Yo'City is an agentic framework for personalized, infinitely expandable 3D city scene generation. It leverages large models with hierarchical planning, a self-critic image synthesis loop, and relationship-guided expansion for spatially coherent growth. Yo'City outperforms existing methods.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.18734
• PDF: https://arxiv.org/pdf/2511.18734
==================================
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✨RAISECity: A Multimodal Agent Framework for Reality-Aligned 3D World Generation at City-Scale
📝 Summary:
RAISECity uses an agentic framework with multimodal tools for reality-aligned, high-quality, city-scale 3D world generation. It iteratively refines scenes, achieving superior precision and fidelity compared to existing methods.
🔹 Publication Date: Published on Nov 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.18005
• PDF: https://arxiv.org/pdf/2511.18005
• Github: https://github.com/tsinghua-fib-lab/RAISECity
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📝 Summary:
RAISECity uses an agentic framework with multimodal tools for reality-aligned, high-quality, city-scale 3D world generation. It iteratively refines scenes, achieving superior precision and fidelity compared to existing methods.
🔹 Publication Date: Published on Nov 22
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.18005
• PDF: https://arxiv.org/pdf/2511.18005
• Github: https://github.com/tsinghua-fib-lab/RAISECity
==================================
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✨LATTICE: Democratize High-Fidelity 3D Generation at Scale
📝 Summary:
LATTICE is a framework for high-fidelity 3D generation using VoxSet, a compact semi-structured representation. It employs a two-stage pipeline with a rectified flow transformer, achieving efficient, scalable, and high-quality 3D creation.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.03052
• PDF: https://arxiv.org/pdf/2512.03052
• Project Page: https://lattice3d.github.io/
• Github: https://github.com/Zeqiang-Lai/LATTICE
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📝 Summary:
LATTICE is a framework for high-fidelity 3D generation using VoxSet, a compact semi-structured representation. It employs a two-stage pipeline with a rectified flow transformer, achieving efficient, scalable, and high-quality 3D creation.
🔹 Publication Date: Published on Nov 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.03052
• PDF: https://arxiv.org/pdf/2512.03052
• Project Page: https://lattice3d.github.io/
• Github: https://github.com/Zeqiang-Lai/LATTICE
==================================
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❤1
✨UltraShape 1.0: High-Fidelity 3D Shape Generation via Scalable Geometric Refinement
📝 Summary:
UltraShape 1.0 is a 3D diffusion framework that generates high-fidelity shapes using a two-stage process: coarse then refined geometry. It includes a novel data pipeline improving dataset quality, enabling strong geometric results on public data.
🔹 Publication Date: Published on Dec 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.21185
• PDF: https://arxiv.org/pdf/2512.21185
• Project Page: https://pku-yuangroup.github.io/UltraShape-1.0/
• Github: https://pku-yuangroup.github.io/UltraShape-1.0/
🔹 Models citing this paper:
• https://huggingface.co/infinith/UltraShape
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📝 Summary:
UltraShape 1.0 is a 3D diffusion framework that generates high-fidelity shapes using a two-stage process: coarse then refined geometry. It includes a novel data pipeline improving dataset quality, enabling strong geometric results on public data.
🔹 Publication Date: Published on Dec 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.21185
• PDF: https://arxiv.org/pdf/2512.21185
• Project Page: https://pku-yuangroup.github.io/UltraShape-1.0/
• Github: https://pku-yuangroup.github.io/UltraShape-1.0/
🔹 Models citing this paper:
• https://huggingface.co/infinith/UltraShape
==================================
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✨Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation
📝 Summary:
DiffusionGS is a novel single-stage 3D diffusion model that directly generates 3D Gaussian point clouds from a single image. It ensures strong view consistency from any prompt view. This method achieves superior quality and is over 5x faster than state-of-the-art techniques.
🔹 Publication Date: Published on Nov 21, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2411.14384
• PDF: https://arxiv.org/pdf/2411.14384
• Project Page: https://caiyuanhao1998.github.io/project/DiffusionGS/
• Github: https://github.com/caiyuanhao1998/Open-DiffusionGS
🔹 Models citing this paper:
• https://huggingface.co/CaiYuanhao/DiffusionGS
✨ Datasets citing this paper:
• https://huggingface.co/datasets/CaiYuanhao/DiffusionGS
==================================
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#3DGeneration #DiffusionModels #GaussianSplatting #ComputerVision #AIResearch
📝 Summary:
DiffusionGS is a novel single-stage 3D diffusion model that directly generates 3D Gaussian point clouds from a single image. It ensures strong view consistency from any prompt view. This method achieves superior quality and is over 5x faster than state-of-the-art techniques.
🔹 Publication Date: Published on Nov 21, 2024
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2411.14384
• PDF: https://arxiv.org/pdf/2411.14384
• Project Page: https://caiyuanhao1998.github.io/project/DiffusionGS/
• Github: https://github.com/caiyuanhao1998/Open-DiffusionGS
🔹 Models citing this paper:
• https://huggingface.co/CaiYuanhao/DiffusionGS
✨ Datasets citing this paper:
• https://huggingface.co/datasets/CaiYuanhao/DiffusionGS
==================================
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arXiv.org
Baking Gaussian Splatting into Diffusion Denoiser for Fast and...
Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt view direction...