✨3D Gaussian Splatting for Real-Time Radiance Field Rendering

📝 Summary:
This paper introduces a method using 3D Gaussians for scene representation to achieve state-of-the-art, high-quality real-time novel-view synthesis at 1080p resolution. It optimizes anisotropic Gaussians and uses a fast rendering algorithm, outperforming previous radiance field methods.

🔹 Publication Date: Published on Aug 8, 2023

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2308.04079
• PDF: https://arxiv.org/pdf/2308.04079
• Github: https://github.com/graphdeco-inria/gaussian-splatting

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Voxel51/gaussian_splatting

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#3DGaussianSplatting #RadianceFields #ComputerGraphics #RealTimeRendering #NovelViewSynthesis

✨MeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds

📝 Summary:
MeshCoder reconstructs complex 3D objects from point clouds into editable Blender Python scripts using a multimodal LLM. This enables superior shape-to-code reconstruction, intuitive editing via code, and enhances 3D shape understanding.

🔹 Publication Date: Published on Aug 20

🔹 Paper Links:
• arXiv Page: https://arxivexplained.com/papers/meshcoder-llm-powered-structured-mesh-code-generation-from-point-clouds
• PDF: https://arxiv.org/pdf/2508.14879
• Project Page: https://daibingquan.github.io/MeshCoder
• Github: https://daibingquan.github.io/MeshCoder

🔹 Models citing this paper:
• https://huggingface.co/InternRobotics/MeshCoder

✨ Datasets citing this paper:
• https://huggingface.co/datasets/InternRobotics/MeshCoderDataset

==================================

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✓ https://t.me/DataScienceT

#MeshCoder #LLM #3DReconstruction #PointClouds #ComputerGraphics

✨MHR: Momentum Human Rig

📝 Summary:
MHR combines ATLASs decoupled skeleton and shape with a modern rig and Momentum-inspired pose correction. This parametric human body model provides expressive, anatomically plausible human animation with non-linear correctives for AR/VR and graphics applications.

🔹 Publication Date: Published on Nov 19

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.15586
• PDF: https://arxiv.org/pdf/2511.15586

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✓ https://t.me/DataScienceT

#ComputerGraphics #3DAnimation #ARVR #HumanModeling #AnimationTech

✨PartUV: Part-Based UV Unwrapping of 3D Meshes

📝 Summary:
PartUV is a novel UV unwrapping pipeline for noisy AI-generated 3D meshes. It uses part decomposition and geometric heuristics to generate significantly fewer, part-aligned charts with low distortion. PartUV outperforms existing methods in chart count and seam length on diverse datasets.

🔹 Publication Date: Published on Nov 20

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.16659
• PDF: https://arxiv.org/pdf/2511.16659
• Project Page: https://www.zhaoningwang.com/PartUV/

==================================

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#UVUnwrapping #3DMeshes #ComputerGraphics #GeometricProcessing #AI

✨Loomis Painter: Reconstructing the Painting Process

📝 Summary:
This paper proposes a unified diffusion model framework for generating consistent, high-fidelity multi-media painting processes. It uses semantic control and cross-medium style augmentation to replicate human artistic workflows, supported by a new dataset and evaluation metrics.

🔹 Publication Date: Published on Nov 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.17344
• PDF: https://arxiv.org/pdf/2511.17344
• Project Page: https://markus-pobitzer.github.io/lplp/
• Github: https://github.com/Markus-Pobitzer/wlp

🔹 Models citing this paper:
• https://huggingface.co/Markus-Pobitzer/wlp-lora

==================================

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✓ https://t.me/DataScienceT

#DiffusionModels #GenerativeAI #AIArt #ComputerGraphics #MachineLearning

✨Loomis Painter: Reconstructing the Painting Process

📝 Summary:
This paper proposes a unified diffusion model framework for generating consistent, high-fidelity multi-media painting processes. It uses semantic control and cross-medium style augmentation to replicate human artistic workflows, supported by a new dataset and evaluation metrics.

🔹 Publication Date: Published on Nov 21

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.17344
• PDF: https://arxiv.org/pdf/2511.17344
• Project Page: https://markus-pobitzer.github.io/lplp/
• Github: https://github.com/Markus-Pobitzer/wlp

🔹 Models citing this paper:
• https://huggingface.co/Markus-Pobitzer/wlp-lora

==================================

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✓ https://t.me/DataScienceT

#DiffusionModels #GenerativeAI #AIArt #ComputerGraphics #MachineLearning

✨MajutsuCity: Language-driven Aesthetic-adaptive City Generation with Controllable 3D Assets and Layouts

📝 Summary:
MajutsuCity is a language-driven framework for generating 3D urban scenes, offering high structural consistency, stylistic diversity, and controllability. It uses a four-stage pipeline and an interactive editing agent, significantly outperforming existing methods.

🔹 Publication Date: Published on Nov 25

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.20415
• PDF: https://arxiv.org/pdf/2511.20415
• Project Page: https://longhz140516.github.io/MajutsuCity/
• Github: https://github.com/LongHZ140516/MajutsuCity

==================================

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✓ https://t.me/DataScienceT

#GenerativeAI #3DModeling #CityGeneration #ComputerGraphics #DeepLearning

✨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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✓ https://t.me/DataScienceT

#3DGeneration #GenerativeAI #CityGeneration #ProceduralGeneration #ComputerGraphics

✨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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#3DGeneration #GenerativeAI #MultimodalAI #VirtualWorlds #ComputerGraphics

✨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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#3DGeneration #AI #DeepLearning #ComputerGraphics #GenerativeAI

✨ShadowDraw: From Any Object to Shadow-Drawing Compositional Art

📝 Summary:
ShadowDraw generates art where a 3D object's cast shadow completes a partial line drawing into a recognizable image. It optimizes object pose, lighting, and the line drawing for visual coherence and quality. This framework creates compelling shadow art and expands computational visual art design.

🔹 Publication Date: Published on Dec 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.05110
• PDF: https://arxiv.org/pdf/2512.05110

==================================

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✓ https://t.me/DataScienceT

#ComputationalArt #ComputerGraphics #AIArt #DigitalArt #GenerativeArt