Browse > Computer Vision > 3D > 3D Shape Analysis

3D Shape Analysis

5 papers with code · Computer Vision
Subtask of 3D

State-of-the-art leaderboards

No evaluation results yet. Help compare methods by submit evaluation metrics.

Latest papers without code

Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views

18 May 2019Zhizhong Han et al

In contrast, we propose a deep neural network, called Parts4Feature, to learn 3D global features from part-level information in multiple views.

3D SHAPE ANALYSIS

18 May 2019

3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention

17 May 2019Zhizhong Han et al

Then, the content and spatial information of each pair of view nodes are encoded by a novel spatial pattern correlation, where the correlation is computed among latent semantic patterns.

3D SHAPE ANALYSIS

17 May 2019

Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution

ICLR 2019 Min Liu et al

The ground-breaking performance obtained by deep convolutional neural networks (CNNs) for image processing tasks is inspiring research efforts attempting to extend it for 3D geometric tasks.

3D SHAPE ANALYSIS

01 May 2019

Volumetric Convolution: Automatic Representation Learning in Unit Ball

ICLR 2019 Sameera Ramasinghe et al

Convolution is an efficient technique to obtain abstract feature representations using hierarchical layers in deep networks.

3D OBJECT RECOGNITION 3D SHAPE ANALYSIS REPRESENTATION LEARNING

01 May 2019

3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation

1 May 2019Stylianos Moschoglou et al

As a result, linear methods such as Principal Component Analysis (PCA) have been mainly utilized towards 3D shape analysis, despite being unable to capture non-linearities and high frequency details of the 3D face - such as eyelid and lip variations.

3D SHAPE ANALYSIS 3D SHAPE REPRESENTATION IMAGE GENERATION SUPER RESOLUTION

01 May 2019

Non-rigid 3D shape retrieval based on multi-view metric learning

20 Mar 2019Haohao Li et al

The different intrinsic representations (features) focus on different geometric properties to describe the same 3D shape, which makes the representations are related.

3D SHAPE ANALYSIS 3D SHAPE RETRIEVAL METRIC LEARNING

20 Mar 2019

Volumetric Convolution: Automatic Representation Learning in Unit Ball

ICLR 2019 Sameera Ramasinghe et al

Convolution is an efficient technique to obtain abstract feature representations using hierarchical layers in deep networks.

3D OBJECT RECOGNITION 3D SHAPE ANALYSIS REPRESENTATION LEARNING

03 Jan 2019

A Survey on Non-rigid 3D Shape Analysis

25 Dec 2018Hamid Laga

In this chapter, we focus on recent techniques that treated the shape of 3D objects as points in some high dimensional space where paths describe deformations.

3D SHAPE ANALYSIS

25 Dec 2018

Learning Material-Aware Local Descriptors for 3D Shapes

20 Oct 2018Hubert Lin et al

Unfortunately, only a small fraction of shapes in 3D repositories are labeled with physical mate- rials, posing a challenge for learning methods.

3D SHAPE ANALYSIS MATERIAL CLASSIFICATION

20 Oct 2018

Classification of lung nodules in CT images based on Wasserstein distance in differential geometry

30 Jun 2018Min Zhang et al

The Wasserstein distance between the nodules is calculated based on our new spherical optimal mass transport, this new algorithm works directly on sphere by using spherical metric, which is much more accurate and efficient than previous methods.

3D SHAPE ANALYSIS LUNG NODULE CLASSIFICATION

30 Jun 2018