Papers 3D Shape Classification
“3D Shape Classification” 태그가 달린 논문 85편 · 필터 해제
Shape retrieval of non-rigid 3d human models
3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. We extend our recent paper which provided a benchm…
3D Shape Classification3D Shape RetrievalRetrievalDeep Learning for 3D Point Clouds: A Survey
Point cloud learning has lately attracted increasing attention due to its wide applications in many areas, such as computer vision, autonomous driving, and robotics. As a dominating technique in AI, deep learning has bee…
3D Object Detection3D Shape ClassificationAutonomous DrivingDeep Learning+4Enhancing 2D Representation via Adjacent Views for 3D Shape Retrieval
Multi-view shape descriptors obtained from various 2D images are commonly adopted in 3D shape retrieval. One major challenge is that significant shape information are discarded during 2D view rendering through projection…
3D Shape Classification3D Shape RetrievalRetrievalA Topological Nomenclature for 3D Shape Analysis in Connectomics
One of the essential tasks in connectomics is the morphology analysis of neurons and organelles like mitochondria to shed light on their biological properties. However, these biological objects often have tangled parts o…
3D Shape Classification3D Shape RetrievalRetrievalHRGE-Net: Hierarchical Relational Graph Embedding Network for Multi-view 3D Shape Recognition
View-based approach that recognizes 3D shape through its projected 2D images achieved state-of-the-art performance for 3D shape recognition. One essential challenge for view-based approach is how to aggregate the multi-v…
3D Shape Classification3D Shape RecognitionGraph EmbeddingRetrievalView N-gram Network for 3D Object Retrieval
How to aggregate multi-view representations of a 3D object into an informative and discriminative one remains a key challenge for multi-view 3D object retrieval. Existing methods either use view-wise pooling strategies w…
3D Object Retrieval3D Shape Classification3D Shape RetrievalObject+1Rethinking Loss Design for Large-scale 3D Shape Retrieval
Learning discriminative shape representations is a crucial issue for large-scale 3D shape retrieval. In this paper, we propose the Collaborative Inner Product Loss (CIP Loss) to obtain ideal shape embedding that discrimi…
3D Object Retrieval3D Shape Classification3D Shape RetrievalRetrievalRe-Ranking via Metric Fusion for Object Retrieval and Person Re-Identification
This work studies the unsupervised re-ranking procedure for object retrieval and person re-identification with a specific concentration on an ensemble of multiple metrics (or similarities). While the re-ranking step is i…
3D Shape Classification3D Shape RetrievalImage RetrievalPerson Re-Identification+2Deep Sketch-Shape Hashing With Segmented 3D Stochastic Viewing
Sketch-based 3D shape retrieval has been extensively studied in recent works, most of which focus on improving the retrieval accuracy, whilst neglecting the efficiency. In this paper, we propose a novel framework for eff…
3D Shape Classification3D Shape Representation3D Shape RetrievalRetrievalSkeleton-Based Hand Gesture Recognition by Learning SPD Matrices with Neural Networks
In this paper, we propose a new hand gesture recognition method based on skeletal data by learning SPD matrices with neural networks. We model the hand skeleton as a graph and introduce a neural network for SPD matrix le…
3D Shape Classification3D Shape RetrievalGesture RecognitionHand Gesture Recognition+2Equivariant Multi-View Networks
Several popular approaches to 3D vision tasks process multiple views of the input independently with deep neural networks pre-trained on natural images, achieving view permutation invariance through a single round of poo…
3D Shape Classification3D Shape RetrievalRetrievalScene ClassificationNon-rigid 3D shape retrieval based on multi-view metric learning
This study presents a novel multi-view metric learning algorithm, which aims to improve 3D non-rigid shape retrieval. With the development of non-rigid 3D shape analysis, there exist many shape descriptors. The intrinsic…
3D Shape Classification3D Shape RetrievalDiversityMetric Learning+1A Sketch Based 3D Shape Retrieval Approach Based on Efficient Deep Point-to-Subspace Metric Learning
A sketch based 3D shape retrieval
3D Shape Classification3D Shape RetrievalMetric LearningRetrievalMulti-feature Distance Metric Learning for Non-rigid 3D Shape Retrieval
In the past decades, feature-learning-based 3D shape retrieval approaches have been received widespread attention in the computer graphic community. These approaches usually explored the hand-crafted distance metric or c…
3D Shape Classification3D Shape RetrievalMetric LearningRetrievalConvolutional Neural Networks on non-uniform geometrical signals using Euclidean spectral transformation
Convolutional Neural Networks (CNN) have been successful in processing data signals that are uniformly sampled in the spatial domain (e.g., images). However, most data signals do not natively exist on a grid, and in the …
3D Shape Classification3D Shape RetrievalRetrievalSurface ReconstructionLearning a Disentangled Embedding for Monocular 3D Shape Retrieval and Pose Estimation
We propose a novel approach to jointly perform 3D shape retrieval and pose estimation from monocular images.In order to make the method robust to real-world image variations, e.g. complex textures and backgrounds, we lea…
3D Object Retrieval3D Shape Classification3D Shape RetrievalPose Estimation+1Cross-Domain 3D Equivariant Image Embeddings
Spherical convolutional networks have been introduced recently as tools to learn powerful feature representations of 3D shapes. Spherical CNNs are equivariant to 3D rotations making them ideally suited to applications wh…
3D Shape ClassificationNovel View SynthesisObjectPose EstimationPVRNet: Point-View Relation Neural Network for 3D Shape Recognition
Three-dimensional (3D) shape recognition has drawn much research attention in the field of computer vision. The advances of deep learning encourage various deep models for 3D feature representation. For point cloud and m…
3D Shape Classification3D Shape RecognitionRelationRelation Network+1MeshNet: Mesh Neural Network for 3D Shape Representation
Mesh is an important and powerful type of data for 3D shapes and widely studied in the field of computer vision and computer graphics. Regarding the task of 3D shape representation, there have been extensive research eff…
3D Shape Classification3D Shape RepresentationGeneral ClassificationRetrievalAngular Triplet-Center Loss for Multi-view 3D Shape Retrieval
How to obtain the desirable representation of a 3D shape, which is discriminative across categories and polymerized within classes, is a significant challenge in 3D shape retrieval. Most existing 3D shape retrieval metho…
3D Object Retrieval3D Shape Classification3D Shape RetrievalMulti-View 3D Shape Retrieval+2