Salient Object Detection in the Deep Learning Era: An In-Depth Survey
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Updated
Jan 9, 2021
Salient Object Detection in the Deep Learning Era: An In-Depth Survey
Learning Unsupervised Video Object Segmentation through Visual Attention (CVPR19, PAMI20)
Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model. IEEE Transactions on Image Processing (2018)
Contextual Encoder-Decoder Network for Visual Saliency Prediction [Neural Networks 2020]
PySODMetrics: A Simple and Efficient Implementation of Grayscale/Binary Segmentation Metrcis
Revisiting Video Saliency: A Large-scale Benchmark and a New Model (CVPR18, PAMI19)
Unified Image and Video Saliency Modeling (ECCV 2020)
Video Salient Object Detection via Fully Convolutional Networks (TIP18)
A Deep Multi-Level Network for Saliency Prediction. ICPR 2016
Deep Visual Attention Prediction (TIP18)
TranSalNet: Towards perceptually relevant visual saliency prediction. Neurocomputing (2022)
Salient Object Detection Driven by Fixation Prediction (CVPR2018)
Pytorch Implementation of the paper - "Tidying Deep Saliency Prediction Architectures"
[WACV2025] SUM: Saliency Unification through Mamba for Visual Attention Modeling
Salient Object Detection with Pyramid Attention and Salient Edges (CVPR19)
Saliency-guided Visual Attention Modeling. #RSS2022 #SOD #RobotVision
[ICCV 2021] Deep Reinforced Accident Anticipation with Visual Explanation
This research is based on efficient saliency detection using deformable convolutions.
The official PyTorch implementation of IEEE Transactions on Image Processing 2021 paper "Rethinking the U-shape Structure for Salient Object Detection"
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