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SeeThrough: Finding Objects in Heavily Occluded Indoor Scene Images.

, , , , , and . 3DV, page 267-276. IEEE Computer Society, (2018)

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3D-CODED: 3D Correspondences by Deep Deformation., , , , and . ECCV (2), volume 11206 of Lecture Notes in Computer Science, page 235-251. Springer, (2018)Neural Cages for Detail-Preserving 3D Deformations., , , , and . CoRR, (2019)Deep Parametric Shape Predictions Using Distance Fields., , , , and . CVPR, page 558-567. Computer Vision Foundation / IEEE, (2020)Self-Supervised Representation Learning for CAD., , , , and . CVPR, page 21327-21336. IEEE, (2023)Neural Convolutional Surfaces., , , , and . CVPR, page 19311-19320. IEEE, (2022)A Papier-Mâché Approach to Learning 3D Surface Generation., , , , and . CVPR, page 216-224. Computer Vision Foundation / IEEE Computer Society, (2018)Joint Learning of 3D Shape Retrieval and Deformation., , , , , and . CVPR, page 11713-11722. Computer Vision Foundation / IEEE, (2021)As-Plausible-As-Possible: Plausibility-Aware Mesh Deformation Using 2D Diffusion Priors., , , and . CoRR, (2023)DECOR-GAN: 3D Shape Detailization by Conditional Refinement., , , , , and . CoRR, (2020)COALESCE: Component Assembly by Learning to Synthesize Connections., , , , , and . 3DV, page 61-70. IEEE, (2020)