Skyfall-GS is a hybrid framework that generates large‑scale, city‑block‑sized 3D urban scenes by combining satellite imagery for coarse geometry with open‑domain diffusion models for detailed appearance. It uses a curriculum‑driven iterative refinement to improve geometric completeness and photorealistic textures, eliminating the need for costly 3D annotations. Experiments show that Skyfall‑GS achieves better cross‑view geometry consistency and more realistic textures than existing methods.
By Jie-Ying Lee, Yi-Ruei Liu, Shr-Ruei Tsai, Wei-Cheng Chang, Chung-Ho Wu, Jiewen Chan, Zhenjun Zhao, Chieh Hubert Lin, Yu-Lun Liu
MeSS (Mesh-based Scene Synthesis) is a method that generates high‑quality, style‑consistent outdoor scenes using city mesh models as geometric priors. The pipeline first creates geometrically consistent sparse views with Cascaded Outpainting ControlNets, then densifies intermediate views via AGInpaint, and finally removes visual inconsistencies with GCAlign. Simultaneously, a 3D Gaussian Splatting scene is reconstructed from the mesh, enabling diverse rendering styles after synthesis.
By Xuyang Chen, Zhijun Zhai, Kaixuan Zhou, Zengmao Wang, Jianan He, Dong Wang, Yanfeng Zhang, Mingwei Sun, Xuqin Wang, R\"udiger Westermann, Tao Wu, Konrad Schindler, Liqiu Meng
arXiv:2609.10363v1 Announce Type: new
Abstract: SceneHI is a framework that lifts high-resolution, illumination-aware priors from 2D diffusion models to perform 3D texture synthesis. It is the first...
By Athanasios Tragakis, Marco Aversa, Daniela Ivanova, Chaitanya Kaul, Roderick Murray-Smith, Daniele Faccio, Paul Henderson
arXiv:2606.24138v2 Announce Type: replace
Abstract: Generating explicit textured 3D city assets from a single satellite image is important for urban simulation and digital twins. Most prior methods,...
By Tongyan Hua, Dongli Wu, Jinjing Zhu, Yinrui Ren, Zhongcheng Hong, Ying-Cong Chen, Hui Xiong, Wufan Zhao
arXiv:2609.23169v1 Announce Type: new
Abstract: High-quality texture generation is essential for creating realistic and production-ready 3D assets. Recent multi-view diffusion methods have shown prom...
By Yibo Zhang, Ze Yuan, Nan Cao, Li Zhang, Yan-Pei Cao, Yuan-Chen Guo, Rui Ma
arXiv:2605.12957v2 Announce Type: replace
Abstract: Recent developments in generative models and large-scale datasets have substantially advanced 3D world generation, facilitating a broad range of do...
By Hanxin Zhu, Cong Wang, Peiyan Tu, Jiayi Luo, Tianyu He, Xin Jin, Zhibo Chen
JanusMesh introduces a fast, training‑free framework for creating 3D visual illusion meshes that reveal different semantics from various viewpoints. The method splits generation into two stages: a cross‑space dual‑branch denoising process that aligns 3D latents with CLIP guidance and blends Signed Distance Fields for seamless geometry, followed by a view‑conditioned texture synthesis module that aggregates 2D diffusion priors onto the fused mesh. Experiments show that JanusMesh produces highly realistic, dual‑semantic 3D illustrations in only 3–5 minutes, outperforming prior approaches in geometric integrity, semantic recognizability, and efficiency.
By Siang-Ling Zhang, Huai-Hsun Cheng, Tsung-Ju Yang, Yu-Lun Liu
arXiv:2606. 07117v1 Announce Type: cross Abstract: This paper presents Native3D, the first end-to-end 3D scene generation framework that completely bypasses 2D intermediate representations.
By Yibo Liu, Ziwei Zhang, Haozhou Pang, Menghao Li, Lanshan He, Gan Qi
DecomVoxel introduces a guided in‑situ denoising optimization that fuses 3D‑native priors with neural scene reconstruction to improve decompositional scene reconstruction. The method employs an epsilon‑based distillation loss for stable latent refinement and adaptive spatial guidance using occupied and vacant anchors with temporal annealing to reduce hallucinations and spatial drift. Experiments on Replica and ScanNet++ demonstrate that DecomVoxel outperforms state‑of‑the‑art approaches while preserving spatial layout, structural fidelity, and style‑consistent texture, yielding high‑quality textured meshes with clean topology.
By Junfeng Ni, Zirui Zhou, Yixin Chen, Yu Liu, Nan Jiang, Zhifei Yang, Song-Chun Zhu, Siyuan Huang
SpatialCrafter introduces a two‑stage framework for single‑image world modeling that first generates a global 3D proxy using a Point‑anchored Sparse Structure Flow module, then refines appearance with a Generative Deferred Refiner built on a video diffusion model. The method incorporates Parallel Geometry Injection and Proxy‑Aware Corruption training to integrate the proxy without disrupting the pretrained generative manifold, and it is evaluated on a newly constructed dataset of 115K scenes. Experiments demonstrate that SpatialCrafter outperforms existing approaches, reducing long‑term drift and maintaining consistency under rapid camera motion and extreme viewpoints.
By Chuan Fang, Lingteng Qiu, Yixun Liang, Rui Chen, Kunming Luo, Zhaohua Zheng, Tongyuan Bai, Feipeng Tian, Zilong Dong, Zihan Zhou, Ping Tan
Recent diffusion-based pipelines have achieved promising progress in image-to-3D synthesis. However, generating high-fidelity details remains challenging, especially when the input image contains rich...
arXiv:2609.39709v1 Announce Type: new
Abstract: Recent diffusion-based pipelines have achieved promising progress in image-to-3D synthesis. However, generating high-fidelity details remains challengi...
By Junyu Li, Qiuyu Chen, Pengcheng Wang, Shiqi Yang, Alexandra Gomez-Villa, Joost van de Weijer, Ruilin Li, Kai Wang