PhysID: Physics-based Interactive Dynamics from a Single-view Image
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Abstract (arXiv)
Transforming static images into interactive experiences remains a challenging task in computer vision. Tackling this challenge holds the potential to elevate mobile user experiences, notably through interactive and AR/VR applications. Current approaches aim to achieve this either using pre-recorded video responses or requiring multi-view images as input. In this paper, we present PhysID, that streamlines the creation of physics-based interactive dynamics from a single-view image by leveraging large generative models for 3D mesh generation and physical property prediction. This significantly reduces the expertise required for engineering-intensive tasks like 3D modeling and intrinsic property calibration, enabling the process to be scaled with minimal manual intervention. We integrate an on-device physics-based engine for physically plausible real-time rendering with user interactions. PhysID represents a leap forward in mobile-based interactive dynamics, offering real-time, non-deterministic interactions and user-personalization with efficient on-device memory consumption. Experiments evaluate the zero-shot capabilities of various Multimodal Large Language Models (MLLMs) on diverse tasks and the performance of 3D reconstruction models. These results demonstrate the cohesive functioning of all modules within the end-to-end framework, contributing to its effectiveness.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 18 of its 24 references that are in the map. First posted on arXiv 21 Jun 2025.
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18 of 24 references.
References · 18
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6 more
- 2023Honeybee: Locality-enhanced Projector for Multimodal LLMcited by 197
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- 2026TourPhysics: Bringing Physics to World Models for Exploration and Manipulation from a Single Image
- 2026SnapPhysics: A Physics-Aware Scene Graph from a Single View for Interactive Mixed Reality Scenes
- 2025PhysWorld: From Real Videos to World Models of Deformable Objects via Physics-Aware Demonstration Synthesis
- 2025PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generation