SceneTeract is a verification interface that separates semantic action understanding from physical feasibility in indoor 3D scenes. It decomposes activities into atomic actions and performs explicit geometric checks to determine executability, providing diagnostic traces for failures. The system reveals widespread functional and accessibility issues in synthetic scenes, shows that existing VLMs over‑predict action feasibility, and improves VLM performance through post‑training with verifier feedback, with benefits that generalize to real‑world scenes.
By L\'eopold Maillard, Francis Engelmann, Tom Durand, Boxiao Pan, Yang You, Leonidas Guibas, Maks Ovsjanikov
HARMONY is a hierarchical chain-of-thought framework that reconstructs complete 3D indoor scenes from a single monocular image. It combines agentic reasoning with visual geometry foundation models, starting with camera calibration and semantic layout recovery, then placing objects hierarchically while refining geometry with point cloud estimations. The method achieves semantically consistent scenes that align perceptually with the input image, outperforming existing baselines on synthetic and real-world data.
By Shufan Sun, Chen Wang, Enxin Song, Jiatao Gu, Lingjie Liu
arXiv:2609.36380v1 Announce Type: new
Abstract: A 3D scene reconstructed from a single image is most useful when represented not as a rendering or a fixed 3D output, but as an explicit scene program...
By Xirui Li, Peng Shi, Mingwen Dong, Sheng Zhang, Zhuoyan Xu, Dongkyu Lee, Shuaichen Chang, Yi Xiang, Lin Pan, Jiarong Jiang
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.
By Jeonghwan Kim, Yushi Lan, Yongwei Chen, Hieu Trung Nguyen, Chuanyu Pan, Xingang Pan
arXiv:2608.24212v1 Announce Type: new
Abstract: The advancement of Embodied AI necessitates high-quality simulation assets that faithfully mirror the real world. However, transforming raw visual obse...
By Yumeng He, Yichen Song, Xiaotian Yang, Weijia Zhang, Zanwei Zhou, Junru Gong, Xiaokang Yang, Yunbo Wang
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
arXiv:2606. 08402v1 Announce Type: 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.
By Jeonghwan Kim, Yushi Lan, Yongwei Chen, Hieu Trung Nguyen, Chuanyu Pan, Xingang Pan
PhysPlan is a training‑free guidance framework that enhances video diffusion models by incorporating physical awareness through agentic physics simulation. It uses a vision‑language model to generate a Chain‑of‑Visual‑Thought representation of kinematic trajectories and 3D depth, which then drives an object‑centric test‑time optimization that isolates kinematic changes and locks the passive environment. The framework also employs Kinetic Intensity Profiling to adapt hyperparameters to varying physical deformations, and demonstrates superior performance on PhyGenBench and Physics‑IQ benchmarks compared to existing VDM baselines.
By Minh-Loi Nguyen, Xuan-Vu Le, Thanh-Toan Do, Tam V. Nguyen, Minh-Triet Tran, Trung-Nghia Le
arXiv:2610.20560v1 Announce Type: cross
Abstract: 3D object composition is pivotal to digital content creation and robot simulation, while also serving as a critical testbed for physical intelligence...
By Weichen Lyu, Chong Xia, Mingyu Dong, Long Xu, Shengjun Zhang, Yueqi Duan
arXiv:2603. 16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets.
By Hui Shan, Keyang Luo, Ming Li, Sizhe Zheng, Yanwei Fu, Zhen Chen, Xiangru Huang
arXiv:2610.19502v1 Announce Type: new
Abstract: Spatial intelligence requires scalable 3D environments that are both photorealistic and semantically grounded, yet existing indoor datasets are dominat...
By Yuanyuan Gao, Zhirui Liu, Yuning Gong, Yifei Liu, Yifan Zhan, Kuixuan Jiao, Xiaolong Zhou, Yifan Yang, Hongjie Zhang, Xue Yang, Dan Xu, Zhihang Zhong
The advancement of Embodied AI necessitates high-quality simulation assets that faithfully mirror the real world. However, transforming raw visual observations into simulation-ready scenes remains cha...