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Approximate pyramidal shape decomposition

ACM transactions on graphics, 2014-11, Vol.33 (6), p.1-12

2014

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Co-Segmentation of 3D Shapes via Subspace Clustering

Computer graphics forum, 2012-08, Vol.31 (5), p.1703-1713

2012

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Foldabilizing furniture

ACM transactions on graphics, 2015-07, Vol.34 (4), p.1-12

2015

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Learning how objects function via co-analysis of interactions

ACM transactions on graphics, 2016-07, Vol.35 (4), p.1-13

2016

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DINA: Deformable INteraction Analogy

Graphical models, 2024-06, Vol.133, p.101217, Article 101217

2024

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Point cloud completion via structured feature maps using a feedback network

Computational visual media (Beijing), 2023-03, Vol.9 (1), p.71-85

2023

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Construction and fabrication of reversible shape transforms

ACM transactions on graphics, 2018-12, Vol.37 (6), p.1-14

2018

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Learning high-DOF reaching-and-grasping via dynamic representation of gripper-object interaction

ACM transactions on graphics, 2022-07, Vol.41 (4), p.1-14, Article 97

2022

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Graph2Plan: learning floorplan generation from layout graphs

ACM transactions on graphics, 2020-07, Vol.39 (4), p.118:1-118:14, Article 118

2020

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Online Scene CAD Recomposition via Autonomous Scanning

ACM transactions on graphics, 2023-12, Vol.42 (6), p.1-16, Article 251

2023

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Neural Packing: from Visual Sensing to Reinforcement Learning

ACM transactions on graphics, 2023-12, Vol.42 (6), p.1-11, Article 267

2023

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Global-to-local generative model for 3D shapes

ACM transactions on graphics, 2018, Vol.37 (6), p.1-10

2018

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Relationship-Based Point Cloud Completion

IEEE transactions on visualization and computer graphics, 2022-12, Vol.28 (12), p.4940-4950

2022

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Asynchronous Collaborative Autoscanning with Mode Switching for Multi-Robot Scene Reconstruction

ACM transactions on graphics, 2022-12, Vol.41 (6), p.1-13, Article 198

2022

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TAP-Net: transport-and-pack using reinforcement learning

ACM transactions on graphics, 2020-11, Vol.39 (6), p.1-15, Article 232

2020

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RPM-Net: recurrent prediction of motion and parts from point cloud

ACM transactions on graphics, 2019-11, Vol.38 (6), p.1-15

2019

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Relationship templates for creating scene variations

ACM transactions on graphics, 2016-11, Vol.35 (6), p.1-13

2016

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Spatial and Surface Correspondence Field for Interaction Transfer

ACM transactions on graphics, 2024-07, Vol.43 (4), p.1-12, Article 83

2024

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Scene-Aware Activity Program Generation with Language Guidance

ACM transactions on graphics, 2023-12, Vol.42 (6), p.1-16, Article 252

2023

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Interaction-Driven Active 3D Reconstruction with Object Interiors

ACM transactions on graphics, 2023-12, Vol.42 (6), p.1-12, Article 250

2023

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Localization and Completion for 3D Object Interactions

IEEE transactions on visualization and computer graphics, 2020-08, Vol.26 (8), p.2634-2644

2020

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ScanBot: Autonomous Reconstruction via Deep Reinforcement Learning

ACM transactions on graphics, 2023-08, Vol.42 (4), p.1-16, Article 157

2023

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Foreword to the Special Section on Shape Modeling International 2020

Computers & graphics, 2020-08, Vol.90, p.A4-A6

2020

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Dapper: decompose-and-pack for 3D printing

ACM transactions on graphics, 2015-11, Vol.34 (6), p.1-12

2015

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Consistent Two-Flow Network for Tele-Registration of Point Clouds

IEEE transactions on visualization and computer graphics, 2022-12, Vol.28 (12), p.4304-4318

2022

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Approximate pyramidal shape decomposition

Co-Segmentation of 3D Shapes via Subspace Clustering

Foldabilizing furniture

Learning how objects function via co-analysis of interactions

DINA: Deformable INteraction Analogy

Point cloud completion via structured feature maps using a feedback network

Construction and fabrication of reversible shape transforms

Learning high-DOF reaching-and-grasping via dynamic representation of gripper-object interaction

Graph2Plan: learning floorplan generation from layout graphs

Online Scene CAD Recomposition via Autonomous Scanning

Neural Packing: from Visual Sensing to Reinforcement Learning

Global-to-local generative model for 3D shapes

Relationship-Based Point Cloud Completion

Asynchronous Collaborative Autoscanning with Mode Switching for Multi-Robot Scene Reconstruction

TAP-Net: transport-and-pack using reinforcement learning

RPM-Net: recurrent prediction of motion and parts from point cloud

Relationship templates for creating scene variations

Spatial and Surface Correspondence Field for Interaction Transfer

Scene-Aware Activity Program Generation with Language Guidance

Interaction-Driven Active 3D Reconstruction with Object Interiors

Localization and Completion for 3D Object Interactions

ScanBot: Autonomous Reconstruction via Deep Reinforcement Learning

Foreword to the Special Section on Shape Modeling International 2020

Dapper: decompose-and-pack for 3D printing

Consistent Two-Flow Network for Tele-Registration of Point Clouds

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