Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network

Published in

Pattern Recognition(2020)

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TL;DR

An effective spatiotemporal feature alignment network tailored to VSP is developed, mainly including two key sub-networks: a multi-scale deformable convolutional alignment network (MDAN) and a bidirectional convolutionsal Long Short-Term Memory (Bi-ConvLSTM) network.

Authors

Bo Liu

3 papers

Kaihua Zhang

3 papers

Jin Chen

2 papers

Huihui Song

1 papers

Qingshan Liu

2 papers

References57 items

Revisiting Video Saliency Prediction in the Deep Learning Era

TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection

Simple vs complex temporal recurrences for video saliency prediction

EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

RepPoints: Point Set Representation for Object Detection

Video Saliency Prediction Using Enhanced Spatiotemporal Alignment Network

Published in

Pattern Recognition(2020)

External Links:

Generate Graph DownloadPDF

TL;DR

Authors

Bo Liu

3 papers

Kaihua Zhang

3 papers

Jin Chen

2 papers

Huihui Song

1 papers

Qingshan Liu

2 papers

References57 items

Revisiting Video Saliency Prediction in the Deep Learning Era

TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency Detection

Simple vs complex temporal recurrences for video saliency prediction

EDVR: Video Restoration With Enhanced Deformable Convolutional Networks

RepPoints: Point Set Representation for Object Detection

TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution

ADCrowdNet: An Attention-Injective Deformable Convolutional Network for Crowd Understanding

Deformable ConvNets V2: More Deformable, Better Results

Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation

Saliency for Fine-grained Object Recognition in Domains with Scarce Training Data

Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinement

Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation

Deformable Convolutional Neural Networks for Hyperspectral Image Classification

Non-rigid Object Tracking via Deep Multi-scale Spatial-Temporal Discriminative Saliency Maps

Learning to Predict Eye Fixations via Multiresolution Convolutional Neural Networks

Revisiting Video Saliency: A Large-Scale Benchmark and a New Model

Predicting Video Saliency with Object-to-Motion CNN and Two-layer Convolutional LSTM

Video Captioning With Attention-Based LSTM and Semantic Consistency

Pedestrian Detection for UAVs Using Cascade Classifiers and Saliency Maps

Deep Visual Attention Prediction

Dynamic Whitening Saliency

Deformable Convolutional Networks

SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction

What Do Different Evaluation Metrics Tell Us About Saliency Models?

Where Does the Driver Look? Top-Down-Based Saliency Detection in a Traffic Driving Environment

Shallow and Deep Convolutional Networks for Saliency Prediction

SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations

Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

How many bits does it take for a stimulus to be salient?

Predicting eye fixations using convolutional neural networks

Adam: A Method for Stochastic Optimization

Very Deep Convolutional Networks for Large-Scale Image Recognition

Video Saliency Incorporating Spatiotemporal Cues and Uncertainty Weighting

Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images

Actions in the Eye: Dynamic Gaze Datasets and Learnt Saliency Models for Visual Recognition

Learning Video Saliency from Human Gaze Using Candidate Selection

Regularized Feature Reconstruction for Spatio-Temporal Saliency Detection

ImageNet classification with deep convolutional neural networks

Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion

Static and space-time visual saliency detection by self-resemblance.

Actions in context

Dynamic visual attention: searching for coding length increments

Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition

Video summarization using a visual attention model

Graph-Based Visual Saliency

Components of bottom-up gaze allocation in natural images

Realistic avatar eye and head animation using a neurobiological model of visual attention

A Model of Saliency-Based Visual Attention for Rapid Scene Analysis

Video Saliency Prediction Using Spatiotemporal Residual Attentive Networks

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Deepvs: a deep learning based video saliency prediction approach

Saliency-Aware Video Object Segmentation

Evaluating the Effect of Saliency Detection and Attention Manipulation in Human-Robot Interaction

A Novel Multiresolution Spatiotemporal Saliency Detection Model and Its Applications in Image and Video Compression

SUNDAy: Saliency Using Natural Statistics for Dynamic Analysis of Scenes

Field of Study

Computer Science

Journal Information

Name

ArXiv

Volume

abs/2005.00687

Venue Information

Name

Pattern Recognition

Type

journal

URL

http://www.elsevier.com/wps/find/journaldescription.cws_home/328/description#description

Alternate Names

Pattern Recognit