Skip to search formSkip to main contentSkip to account menu
PCANet: A Simple Deep Learning Baseline for Image Classification?
TLDR
Surprisingly, for all tasks, such a seemingly naive PCANet model is on par with the state-of-the-art features either prefixed, highly hand-crafted, or carefully learned [by deep neural networks (DNNs)].
View on IEEE
Learning Compact Binary Descriptors with Unsupervised Deep Neural Networks
TLDR
Experimental results on three different visual analysis tasks including image matching, image retrieval, and object recognition clearly demonstrate the effectiveness of the proposed unsupervised deep learning approach called DeepBit.
View on IEEE
Deep hashing for compact binary codes learning
TLDR
A deep neural network is developed to seek multiple hierarchical non-linear transformations to learn compact binary codes for large scale visual search and shows the superiority of the proposed approach over the state-of-the-arts.
View on IEEE
Neighborhood repulsed metric learning for kinship verification
TLDR
A new neighborhood repulsed metric learning (NRML) method for kinship verification from facial images is proposed and the experimental results show that the methods are comparable to that of human observers.
View on PubMed
Discriminative Deep Metric Learning for Face Verification in the Wild
TLDR
The proposed DDML trains a deep neural network which learns a set of hierarchical nonlinear transformations to project face pairs into the same feature subspace, under which the distance of each positive face pair is less than a smaller threshold and that of each negative pair is higher than a larger threshold.
View on IEEE
A Siamese Long Short-Term Memory Architecture for Human Re-identification
TLDR
A novel siamese Long Short-Term Memory (LSTM) architecture that can process image regions sequentially and enhance the discriminative capability of local feature representation by leveraging contextual information.
View PDF on arXiv
Neighborhood repulsed metric learning for kinship verification
TLDR
This paper proposes a new neighborhood repulsed metric learning (NRML) method for kinship verification, and proposes a multiview NRM-L method to seek a common distance metric to make better use of multiple feature descriptors to further improve the verification performance.
View on IEEE
Discriminative Multimanifold Analysis for Face Recognition from a Single Training Sample per Person
TLDR
This paper proposes a novel discriminative multimanifold analysis (DMMA) method by learning discrim inative features from image patches by partitioning each enrolled face image into several nonoverlapping patches to form an image set for each sample per person.
View on IEEE
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition
TLDR
A deep progressive reinforcement learning (DPRL) method for action recognition in skeleton-based videos, which aims to distil the most informative frames and discard ambiguous frames in sequences for recognizing actions.
View on IEEE
Learning Compact Binary Face Descriptor for Face Recognition
TLDR
A compact binary face descriptor (CBFD) feature learning method for face representation and recognition that reduces the modality gap of heterogeneous faces at the feature level to make the method applicable to heterogeneous face recognition.
View on IEEE
...
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License