Fokin, EgorSavva, ManolisMusialski, PrzemyslawLim, Isaak2026-04-202026-04-202026978-3-03868-299-82309-5059https://diglib.eg.org/handle/10.2312/egs20261015https://diglib.eg.org/handle/10.2312/egs20261015Physics-based simulation involves trade-offs between performance and accuracy. In collision detection, one trade-off is the granularity of collider geometry. Primitive-based colliders such as bounding boxes are efficient, while using the original mesh is more accurate but often computationally expensive. Approximate Convex Decomposition (ACD) methods strive for a balance of efficiency and accuracy. Prior works can produce high-quality decompositions but require large numbers of convex parts and are sensitive to the orientation of the input mesh. We address these weaknesses with VisACD, a visibility-based, rotation-equivariant, and intersection-free ACD algorithm with GPU acceleration. Our approach produces high-quality decompositions with fewer convex parts, is not sensitive to shape orientation, and is more efficient than prior work.CC-BY-4.0Collision DetectionMesh ProcessingGPU Computing10.2312/egs.202610154 pages