Hugging Face Trending Papers
Building Rome from a Single Image
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arXiv Computer Vision
1d ago
Building Rome from a Single Image
arXiv:2610.08790v1 Announce Type: new Abstract: Single-image scene generation aims to produce a complete 3D scene mesh from a single image, including surfaces the camera did not observe. While pretra...
arXiv Computer Vision
1d ago
DistScene: Object-to-Scene Distillation for 3D Scene Generation
DistScene is a framework for generating 3D scenes from a single image by jointly modeling the environment and individual objects. It introduces Scene-Frame Generation to produce separate environment and object components in a shared coordinate frame, and Object-Centric Refinement to fine‑tune each object with scene context. The method also employs Object-to-Scene Distillation to transfer pretrained object-generation priors to scene generation using automatically composed synthetic scenes, achieving improved spatial coherence on indoor and outdoor benchmarks.
arXiv Computer Vision
3d ago
T3lescope: Arbitrary-Resolution High-Fidelity Generative Surface Reconstruction from Images
T3lescope is a generative surface reconstruction method that produces high‑fidelity 3D meshes from posed multi‑view images without per‑scene optimization. It uses a single fixed‑resolution generator in a coarse‑to‑fine cascade, where each level refines geometry within progressively finer spatial cells. Trained on cells at multiple scales, the model shares weights across all levels, allowing it to adapt the number of levels, cell scales, and locations at inference time and achieve consistent geometry across indoor, outdoor, and city‑scale scenes.
arXiv Computer Vision
Sep 7
WorldSculpt: Generating Compositional Worlds from Grounded Videos
WorldSculpt presents a method for generating compositional 3D representations of cluttered scenes with hundreds of objects by adapting a single-object 3D generative prior to multi-view observations. The approach, built on Pixal3D with a multi-view conditioning pathway, can generalize to highly occluded scenes without scene-level training. The authors also introduce the UE-MeshyScene benchmark and demonstrate that their method outperforms prior approaches across various evaluation settings, including converting existing 3DGS worlds into compositional mesh scenes.
arXiv Computer Vision
Aug 26
SceneReGen: Generative Reconstruction of 3D Scenes from a Single Image
SceneReGen is a new framework for reconstructing 3D scenes from a single image by generating and assembling complete object meshes within a shared observation‑aligned scene frame. It uses selective pose factorization to encode each object’s observed orientation directly into the generated mesh, while estimating translation and scale from instance‑level and global scene cues. Evaluated on the 3D‑FUTURE dataset, SceneReGen outperforms existing methods on scene‑level metrics and shows strong performance on object‑level metrics, demonstrating its effectiveness in autonomous‑driving and embodied‑AI scenarios.
arXiv AI
Jun 16
SceneConductor: 3D Scene Generation from a Single Image with Multi-Agent Orchestration
arXiv:2606. 08402v2 Announce Type: replace-cross Abstract: Generating complete 3D scenes from a single image requires inferring globally consistent geometry, object relationships, and environmental context from inherently ambiguous visual evidence.