Diorama: Unleashing Zero-shot Single-view 3D Scene Modeling

• URL: http://arxiv.org/abs/2411.19492v1
• Date: Fri, 29 Nov 2024 06:19:04 GMT
• Title: Diorama: Unleashing Zero-shot Single-view 3D Scene Modeling
• Authors: Qirui Wu, Denys Iliash, Daniel Ritchie, Manolis Savva, Angel X. Chang,
• Abstract summary: We present Diorama, the first zero-shot open-world system that holistically models 3D scenes from single-view RGB observations. We show the feasibility of our approach by decomposing the problem into subtasks and introduce robust, generalizable solutions to each.
• Score: 27.577720075952225
• License:
• Abstract: Reconstructing structured 3D scenes from RGB images using CAD objects unlocks efficient and compact scene representations that maintain compositionality and interactability. Existing works propose training-heavy methods relying on either expensive yet inaccurate real-world annotations or controllable yet monotonous synthetic data that do not generalize well to unseen objects or domains. We present Diorama, the first zero-shot open-world system that holistically models 3D scenes from single-view RGB observations without requiring end-to-end training or human annotations. We show the feasibility of our approach by decomposing the problem into subtasks and introduce robust, generalizable solutions to each: architecture reconstruction, 3D shape retrieval, object pose estimation, and scene layout optimization. We evaluate our system on both synthetic and real-world data to show we significantly outperform baselines from prior work. We also demonstrate generalization to internet images and the text-to-scene task.

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