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NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis
TLDR
A large-scale dataset for RGB+D human action recognition with more than 56 thousand video samples and 4 million frames, collected from 40 distinct subjects is introduced and a new recurrent neural network structure is proposed to model the long-term temporal correlation of the features for each body part, and utilize them for better action classification. Expand
Deep Learning-Based Classification of Hyperspectral Data
TLDR
The concept of deep learning is introduced into hyperspectral data classification for the first time, and a new way of classifying with spatial-dominated information is proposed, which is a hybrid of principle component analysis (PCA), deep learning architecture, and logistic regression. Expand
Spatio-Temporal LSTM with Trust Gates for 3D Human Action Recognition
TLDR
This paper introduces new gating mechanism within LSTM to learn the reliability of the sequential input data and accordingly adjust its effect on updating the long-term context information stored in the memory cell, and proposes a more powerful tree-structure based traversal method. Expand
Gated Siamese Convolutional Neural Network Architecture for Human Re-identification
TLDR
A gating function is proposed to selectively emphasize such fine common local patterns that may be essential to distinguish positive pairs from hard negative pairs by comparing the mid-level features across pairs of images. Expand
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
TLDR
This work introduces a large-scale dataset for RGB+D human action recognition, which is collected from 106 distinct subjects and contains more than 114 thousand video samples and 8 million frames, and investigates a novel one-shot 3D activity recognition problem on this dataset. Expand
Progressive Attention Guided Recurrent Network for Salient Object Detection
TLDR
A novel attention guided network which selectively integrates multi-level contextual information in a progressive manner and introduces multi-path recurrent feedback to enhance this proposed progressive attention driven framework. Expand
Solving Systems of Random Quadratic Equations via Truncated Amplitude Flow
TLDR
This paper presents a new algorithm, termed Truncated amplitude flow (TAF), to recover an unknown vector from a system of quadratic equations, and proves that as soon as the number of equations is on the order of theNumber of unknowns, TAF recovers the solution exactly. Expand
A Bi-Directional Message Passing Model for Salient Object Detection
TLDR
This paper proposes a novel bi-directional message passing model to integrate multi-level features for salient object detection, and adopts a Multi-scale Context-aware Feature Extraction Module (MCFEM) for multi- level feature maps to capture rich context information. Expand
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. Expand
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