
Vector Neurons: A General Framework for SO(3)Equivariant Networks
Invariance and equivariance to the rotation group have been widely discu...
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Spectral Unions of Partial Deformable 3D Shapes
Spectral geometric methods have brought revolutionary changes to the fie...
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Joint Learning of 3D Shape Retrieval and Deformation
We propose a novel technique for producing highquality 3D models that m...
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Quantum Permutation Synchronization
We present QuantumSync, the first quantum algorithm for solving a synchr...
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ArtEmis: Affective Language for Visual Art
We present a novel largescale dataset and accompanying machine learning...
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Deep Bingham Networks: Dealing with Uncertainty and Ambiguity in Pose Estimation
In this work, we introduce Deep Bingham Networks (DBN), a generic framew...
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Robust Neural Routing Through Space Partitions for Camera Relocalization in Dynamic Indoor Environments
Localizing the camera in a known indoor environment is a key building bl...
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Active Visual Localization in Partially Calibrated Environments
Humans can robustly localize themselves without a map after they get los...
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Generative Layout Modeling using Constraint Graphs
We propose a new generative model for layout generation. We generate lay...
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ShapeFlow: Learnable Deformations Among 3D Shapes
We present ShapeFlow, a flowbased model for learning a deformation spac...
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Generative 3D Part Assembly via Dynamic Graph Learning
Autonomous part assembly is a challenging yet crucial task in 3D compute...
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Robust Learning Through CrossTask Consistency
Visual perception entails solving a wide set of tasks, e.g., object dete...
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ManifoldPlus: A Robust and Scalable Watertight Manifold Surface Generation Method for Triangle Soups
We present ManifoldPlus, a method for robust and scalable conversion of ...
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MeshODE: A Robust and Scalable Framework for Mesh Deformation
We present MeshODE, a scalable and robust framework for pairwise CAD mod...
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6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference
We present a multimodal camera relocalization framework that captures am...
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DeformationAware 3D Model Embedding and Retrieval
We introduce a new problem of retrieving 3D models that are deformable t...
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Synchronizing Probability Measures on Rotations via Optimal Transport
We introduce a new paradigm, measure synchronization, for synchronizing ...
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Learning 3D Part Assembly from a Single Image
Autonomous assembly is a crucial capability for robots in many applicati...
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Adversarial Texture Optimization from RGBD Scans
Realistic color texture generation is an important step in RGBD surface...
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Representation Learning Through Latent Canonicalizations
We seek to learn a representation on a large annotated data source that ...
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Continuous Geodesic Convolutions for Learning on 3D Shapes
The majority of descriptorbased methods for geometric processing of non...
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The Whole Is Greater Than the Sum of Its Nonrigid Parts
According to Aristotle, a philosopher in Ancient Greece, "the whole is g...
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From Planes to Corners: MultiPurpose Primitive Detection in Unorganized 3D Point Clouds
We propose a new method for segmentationfree joint estimation of orthog...
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SideTuning: Network Adaptation via Additive Side Networks
When training a neural network for a desired task, one may prefer to ada...
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Quaternion Equivariant Capsule Networks for 3D Point Clouds
We present a 3D capsule architecture for processing of point clouds that...
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CategoryLevel Articulated Object Pose Estimation
This paper addresses the task of categorylevel pose estimation for arti...
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Learning to Navigate Using MidLevel Visual Priors
How much does having visual priors about the world (e.g. the fact that t...
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Joint Embedding of 3D Scan and CAD Objects
3D scan geometry and CAD models often contain complementary information ...
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Which Tasks Should Be Learned Together in Multitask Learning?
Many computer vision applications require solving multiple tasks in real...
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OperatorNet: Recovering 3D Shapes From Difference Operators
This paper proposes a learningbased framework for reconstructing 3D sha...
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FrameNet: Learning Local Canonical Frames of 3D Surfaces from a Single RGB Image
In this work, we introduce the novel problem of identifying dense canoni...
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CoSegNet: Deep CoSegmentation of 3D Shapes with Group Consistency Loss
We introduce CoSegNet, a deep neural network architecture for cosegment...
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Learning Transformation Synchronization
Reconstructing the 3D model of a physical object typically requires us t...
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Composite Shape Modeling via Latent Space Factorization
We present a novel neural network architecture, termed DecomposerCompos...
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MidLevel Visual Representations Improve Generalization and Sample Efficiency for Learning Active Tasks
One of the ultimate promises of computer vision is to help robotic agent...
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GSPN: Generative Shape Proposal Network for 3D Instance Segmentation in Point Cloud
We introduce a novel 3D object proposal approach named Generative Shape ...
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TextureNet: Consistent Local Parametrizations for Learning from HighResolution Signals on Meshes
We introduce, TextureNet, a neural network architecture designed to extr...
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Supervised Fitting of Geometric Primitives to 3D Point Clouds
Fitting geometric primitives to 3D point cloud data bridges a gap betwee...
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Deep Part Induction from Articulated Object Pairs
Object functionality is often expressed through part articulation  as ...
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Learning Fuzzy Set Representations of Partial Shapes on Dual Embedding Spaces
Modeling relations between components of 3D objects is essential for man...
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Latent Space Representation for Shape Analysis and Learning
We propose a novel shape representation useful for analyzing and process...
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PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks
Deep learning systems have become ubiquitous in many aspects of our live...
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Deep Functional Dictionaries: Learning Consistent Semantic Structures on 3D Models from Functions
Various 3D semantic attributes such as segmentation masks, geometric fea...
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Taskonomy: Disentangling Task Transfer Learning
Do visual tasks have a relationship, or are they unrelated? For instance...
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Graph Matching with Anchor Nodes: A Learning Approach
In this paper, we consider the weighted graph matching problem with part...
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Robust Watertight Manifold Surface Generation Method for ShapeNet Models
In this paper, we describe a robust algorithm for 2Manifold generation ...
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LargeScale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
We introduce a largescale 3D shape understanding benchmark using data a...
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ComplementMe: WeaklySupervised Component Suggestions for 3D Modeling
Assemblybased tools provide a powerful modeling paradigm for nonexpert...
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Learning Representations and Generative Models for 3D Point Clouds
Threedimensional geometric data offer an excellent domain for studying ...
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GRASS: Generative Recursive Autoencoders for Shape Structures
We introduce a novel neural network architecture for encoding and synthe...
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