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Multi-View 3D Object Retrieval With Deep Embedding Network

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

Sep 23, 2016

Haiyun GuoHanqing Lu

Abstract

In multi-view 3D object retrieval, each object is characterized by a group of 2D images captured from different views. Rather than using hand-crafted features, in this paper, we take advantage of the strong discriminative power of convolutional neural network to learn an effective 3D ob...read more

Mentioned in this Paper

Biological Neural Networks
Classification
2-Dimensional
Three-dimensional
Anatomical Space Structure
Objective (Goal)
Neural Network Simulation
Triplet, Centriole
Embedding
Description
Paper Details
References

Multi-View 3D Object Retrieval With Deep Embedding Network

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

Sep 23, 2016

Haiyun GuoHanqing Lu

PMID: 27654482

DOI: 10.1109/tip.2016.2609814

Abstract

In multi-view 3D object retrieval, each object is characterized by a group of 2D images captured from different views. Rather than using hand-crafted features, in this paper, we take advantage of the strong discriminative power of convolutional neural network to learn an effective 3D ob...read more

Mentioned in this Paper

Biological Neural Networks
Classification
2-Dimensional
Three-dimensional
Anatomical Space Structure
Objective (Goal)
Neural Network Simulation
Triplet, Centriole
Embedding
Description
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