Group Invariant Deep Representations for Image Instance Retrieval
Most image instance retrieval pipelines are based on comparison of vectors known as global image descriptors between a query image and the database images. Due to their success in large scale image classification, representations extracted from Convolutional Neural Networks (CNN) are quickly gaining...
Main Authors: | Morère, Olivier, Veillard, Antoine, Lin, Jie, Petta, Julie, Chandrasekhar, Vijay, Poggio, Tomaso |
---|---|
Format: | Technical Report |
Language: | en_US |
Published: |
Center for Brains, Minds and Machines (CBMM)
2016
|
Subjects: | |
Online Access: | http://hdl.handle.net/1721.1/100796 |
Similar Items
-
Nested Invariance Pooling and RBM Hashing for Image Instance Retrieval
by: Morère, Olivier, et al.
Published: (2017) -
Foveation-based Mechanisms Alleviate Adversarial Examples
by: Lou, Yan, et al.
Published: (2016) -
Compression of Deep Neural Networks for Image Instance Retrieval
by: Chandrasekhar, Vijay, et al.
Published: (2017) -
Rotation Invariant Object Recognition from One Training Example
by: Yokono, Jerry Jun, et al.
Published: (2004) -
Rotation Invariant Object Recognition from One Training Example
by: Yokono, Jerry Jun, et al.
Published: (2005)