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03/03/2023
Unsupervised 3D Shape Reconstruction by Part Retrieval and Assembly
Representing a 3D shape with a set of primitives can aid perception of s...
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07/24/2022
PatchRD: Detail-Preserving Shape Completion by Learning Patch Retrieval and Deformation
This paper introduces a data-driven shape completion approach that focus...
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05/05/2022
Neural Jacobian Fields: Learning Intrinsic Mappings of Arbitrary Meshes
This paper introduces a framework designed to accurately predict piecewi...
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12/01/2021
The Shape Part Slot Machine: Contact-based Reasoning for Generating 3D Shapes from Parts
We present the Shape Part Slot Machine, a new method for assembling nove...
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11/23/2021
ReGroup: Recursive Neural Networks for Hierarchical Grouping of Vector Graphic Primitives
Selection functionality is as fundamental to vector graphics as it is fo...
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11/12/2021
Temporally-Consistent Surface Reconstruction using Metrically-Consistent Atlases
We propose a method for unsupervised reconstruction of a temporally-cons...
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10/11/2021
BuildingNet: Learning to Label 3D Buildings
We introduce BuildingNet: (a) a large-scale dataset of 3D building model...
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08/06/2021
GLASS: Geometric Latent Augmentation for Shape Spaces
We investigate the problem of training generative models on a very spars...
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04/14/2021
Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases
We propose a method for the unsupervised reconstruction of a temporally-...
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02/15/2021
A Unified Batch Selection Policy for Active Metric Learning
Active metric learning is the problem of incrementally selecting high-ut...
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01/19/2021
Joint Learning of 3D Shape Retrieval and Deformation
We propose a novel technique for producing high-quality 3D models that m...
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05/20/2020
Batch Decorrelation for Active Metric Learning
We present an active learning strategy for training parametric models of...
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05/04/2020
Neural Subdivision
This paper introduces Neural Subdivision, a novel framework for data-dri...
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03/26/2020
ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds
We propose a novel, end-to-end trainable, deep network called ParSeNet t...
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03/19/2020
Affinity Graph Supervision for Visual Recognition
Affinity graphs are widely used in deep architectures, including graph c...
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12/13/2019
Neural Cages for Detail-Preserving 3D Deformations
We propose a novel learnable representation for detail-preserving shape ...
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05/27/2019
FAN: Focused Attention Networks
Attention networks show promise for both vision and language tasks, by e...
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05/08/2019
PerceptNet: Learning Perceptual Similarity of Haptic Textures in Presence of Unorderable Triplets
In order to design haptic icons or build a haptic vocabulary, we require...
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03/27/2019
BAE-NET: Branched Autoencoder for Shape Co-Segmentation
We treat shape co-segmentation as a representation learning problem and ...
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03/25/2019
CoSegNet: Deep Co-Segmentation of 3D Shapes with Group Consistency Loss
We introduce CoSegNet, a deep neural network architecture for co-segment...
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10/20/2018
Learning Material-Aware Local Descriptors for 3D Shapes
Material understanding is critical for design, geometric modeling, and a...
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09/14/2018
SCORES: Shape Composition with Recursive Substructure Priors
We introduce SCORES, a recursive neural network for shape composition. O...
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07/24/2018
GRAINS: Generative Recursive Autoencoders for INdoor Scenes
We present a generative neural network which enables us to generate plau...
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04/28/2018
Generalizing Across Domains via Cross-Gradient Training
We present CROSSGRAD, a method to use multi-domain training data to lear...
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12/09/2017
A Deep Recurrent Framework for Cleaning Motion Capture Data
We present a deep, bidirectional, recurrent framework for cleaning noisy...
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08/22/2017
Tags2Parts: Discovering Semantic Regions from Shape Tags
We propose a novel method for discovering shape regions that strongly co...
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08/06/2017
ComplementMe: Weakly-Supervised Component Suggestions for 3D Modeling
Assembly-based tools provide a powerful modeling paradigm for non-expert...
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06/14/2017
Learning Local Shape Descriptors from Part Correspondences With Multi-view Convolutional Networks
We present a new local descriptor for 3D shapes, directly applicable to ...
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05/05/2017
GRASS: Generative Recursive Autoencoders for Shape Structures
We introduce a novel neural network architecture for encoding and synthe...
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12/08/2016