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Continuous Curve Textures
Repetitive patterns are ubiquitous in natural and human-made objects, an...
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Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces
Reconstructing continuous surfaces from 3D point clouds is a fundamental...
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Improved Modeling of 3D Shapes with Multi-view Depth Maps
We present a simple yet effective general-purpose framework for modeling...
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DRWR: A Differentiable Renderer without Rendering for Unsupervised 3D Structure Learning from Silhouette Images
Differentiable renderers have been used successfully for unsupervised 3D...
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Fine-Grained 3D Shape Classification with Hierarchical Part-View Attentions
Fine-grained 3D shape classification is important and research challengi...
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LRC-Net: Learning Discriminative Features on Point Clouds by Encoding Local Region Contexts
Learning discriminative feature directly on point clouds is still challe...
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LRC-Net: Learning Discriminative Features on Point Clouds by EncodingLocal Region Contexts
Learning discriminative feature directly on point clouds is still challe...
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SeqXY2SeqZ: Structure Learning for 3D Shapes by Sequentially Predicting 1D Occupancy Segments From 2D Coordinates
Structure learning for 3D shapes is vital for 3D computer vision. State-...
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ORCSolver: An Efficient Solver for Adaptive GUI Layout with OR-Constraints
OR-constrained (ORC) graphical user interface layouts unify conventional...
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Learning Generative Models using Denoising Density Estimators
Learning generative probabilistic models that can estimate the continuou...
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Learning to Generate Dense Point Clouds with Textures on Multiple Categories
3D reconstruction from images is a core problem in computer vision. With...
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SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization
We propose SDFDiff, a novel approach for image-based shape optimization ...
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3D Shape Completion with Multi-view Consistent Inference
3D shape completion is important to enable machines to perceive the comp...
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L2G Auto-encoder: Understanding Point Clouds by Local-to-Global Reconstruction with Hierarchical Self-Attention
Auto-encoder is an important architecture to understand point clouds in ...
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ShapeCaptioner: Generative Caption Network for 3D Shapes by Learning a Mapping from Parts Detected in Multiple Views to Sentences
3D shape captioning is a challenging application in 3D shape understandi...
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Multi-Angle Point Cloud-VAE: Unsupervised Feature Learning for 3D Point Clouds from Multiple Angles by Joint Self-Reconstruction and Half-to-Half Prediction
Unsupervised feature learning for point clouds has been vital for large-...
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Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views
Deep learning has achieved remarkable results in 3D shape analysis by le...
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3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention
Learning global features by aggregating information over multiple views ...
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Render4Completion: Synthesizing Multi-view Depth Maps for 3D Shape Completion
We propose a novel approach for 3D shape completion by synthesizing mult...
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Smart, Deep Copy-Paste
In this work, we propose a novel system for smart copy-paste, enabling t...
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Understanding the (un)interpretability of natural image distributions using generative models
Probability density estimation is a classical and well studied problem, ...
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Video Synthesis from a Single Image and Motion Stroke
In this paper, we propose a new method to automatically generate a video...
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Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences
A recent method employs 3D voxels to represent 3D shapes, but this limit...
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View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions
In this paper we present a novel unsupervised representation learning ap...
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Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-based Sequence to Sequence Network
Exploring contextual information in the local region is important for sh...
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Learning to Importance Sample in Primary Sample Space
Importance sampling is one of the most widely used variance reduction st...
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Specular-to-Diffuse Translation for Multi-View Reconstruction
Most multi-view 3D reconstruction algorithms, especially when shape-from...
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FaceShop: Deep Sketch-based Face Image Editing
We present a novel system for sketch-based face image editing, enabling ...
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Disentangling Factors of Variation by Mixing Them
We propose an unsupervised approach to learn image representations that ...
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Challenges in Disentangling Independent Factors of Variation
We study the problem of building models that disentangle independent fac...
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Deep Mean-Shift Priors for Image Restoration
In this paper we introduce a natural image prior that directly represent...
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Image Restoration using Autoencoding Priors
We propose to leverage denoising autoencoder networks as priors to addre...
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Temporally Consistent Motion Segmentation from RGB-D Video
We present a method for temporally consistent motion segmentation from R...
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