SceneGit: a practical system for diffing and merging 3D environments

Version control systems are the foundation of collaborative workflows for text documents. For 3D environments though, version control is still an open problem due to the heterogeneous data of 3D scenes and their size. In this paper, we present a practical version control system for 3D scenes comprised of shapes, materials, textures, and animations, combined together in scene graphs. We version objects at their finest granularity, to make repositories smaller and to allow artists to work concurrently on the same object. Since, for some scene data, computing an optimal set of changes between versions is not computationally feasible, version control systems use heuristics. Compared to prior work, we propose heuristics that are efficient, robust, and independent of the application. We test our system on a variety of large scenes edited with different workflows, and show that our approach can handle all cases well while remaining efficient as scene size increases. Compared to prior work, we are significantly faster and more robust. A user study confirms that our system aids collaboration

SceneGit: a practical system for diffing and merging 3D environments

Version control systems are the foundation of collaborative workflows for text documents. For 3D environments though, version control is still an open problem due to the heterogeneous data of 3D scenes and their size. In this paper, we present a practical version control system for 3D scenes comprised of shapes, materials, textures, and animations, combined together in scene graphs. We version objects at their finest granularity, to make repositories smaller and to allow artists to work concurrently on the same object. Since, for some scene data, computing an optimal set of changes between versions is not computationally feasible, version control systems use heuristics. Compared to prior work, we propose heuristics that are efficient, robust, and independent of the application. We test our system on a variety of large scenes edited with different workflows, and show that our approach can handle all cases well while remaining efficient as scene size increases. Compared to prior work, we are significantly faster and more robust. A user study confirms that our system aids collaboration