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The Neurally-Guided Shape Parser: Grammar-based Labeling of 3D Shape Regions with Approximate Inference.

, , , and . CVPR, page 11604-11613. IEEE, (2022)

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Improving Unsupervised Visual Program Inference with Code Rewriting Families., , and . ICCV, page 15745-15755. IEEE, (2023)ShapeMOD: Macro Operation Discovery for 3D Shape Programs, , , , and . (2021)cite arxiv:2104.06392Comment: Project Page: https://rkjones4.github.io/shapeMOD.html.Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases., , , , , , , , , and . CoRR, (2024)The Neurally-Guided Shape Parser: A Monte Carlo Method for Hierarchical Labeling of Over-segmented 3D Shapes., , and . CoRR, (2021)PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributions., , and . CVPR, page 9861-9870. IEEE, (2022)ShapeAssembly: learning to generate programs for 3D shape structure synthesis., , , , , , , and . ACM Trans. Graph., 39 (6): 234:1-234:20 (2020)Learning to Infer Shape Programs Using Latent Execution Self Training., , and . CoRR, (2020)Learning to Infer Generative Template Programs for Visual Concepts., , and . CoRR, (2024)The Neurally-Guided Shape Parser: Grammar-based Labeling of 3D Shape Regions with Approximate Inference., , , and . CVPR, page 11604-11613. IEEE, (2022)ParSEL: Parameterized Shape Editing with Language., , , , and . CoRR, (2024)