SOTAVerified

Saliency Detection

Saliency Detection is a preprocessing step in computer vision which aims at finding salient objects in an image.

Source: An Unsupervised Game-Theoretic Approach to Saliency Detection

Papers

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Showing 176–200 of 364 papers

TitleStatusHype
Unsupervised Discovery of Interpretable Directions in the GAN Latent SpaceCode1
An Analysis of Object Representations in Deep Visual Trackers—0
A General Framework for Saliency Detection Methods—0
cmSalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial NetworksCode0
SaLite : A light-weight model for salient object detectionCode0
DeepUSPS: Deep Robust Unsupervised Saliency Prediction via Self-supervision—0
Memory-oriented Decoder for Light Field Salient Object DetectionCode0
CAGNet: Content-Aware Guidance for Salient Object DetectionCode1
Boosting Object Recognition in Point Clouds by Saliency Detection—0
An End-to-End Network for Co-Saliency Detection in One Single Image—0
Context-Aware Saliency Detection for Image Retargeting Using Convolutional Neural Networks—0
Deep Learning for Light Field Saliency Detection—0
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency DetectionCode0
DeepUSPS: Deep Robust Unsupervised Saliency Prediction With Self-Supervision—0
Inducing Stronger Object Representations in Deep Visual Trackers—0
CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse—0
Motion Guided Attention for Video Salient Object DetectionCode0
Joint Learning of Saliency Detection and Weakly Supervised Semantic SegmentationCode0
Towards High-Resolution Salient Object DetectionCode0
In defense of OSVOS—0
TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency DetectionCode0
Contour Loss: Boundary-Aware Learning for Salient Object Segmentation—0
Region Refinement Network for Salient Object Detection—0
Saliency Detection With Fully Convolutional Neural Network—0
Light Field Saliency Detection with Deep Convolutional NetworksCode0
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All datasetsDUT-OMRONHKU-ISCAT2000DUTS-testECSSDPASCAL ContextPASCAL-S

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UCFMAE0.12—Unverified
2U2-Net+MAE0.06—Unverified
3U2-NetMAE0.05—Unverified
4LDF(ours)MAE0.05—Unverified
5Pyramid Feature AttentionMAE0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1U2-Net+MAE0.04—Unverified
2Pyramid Feature AttentionMAE0.03—Unverified
3LDF(ours)MAE0.03—Unverified
#ModelMetricClaimedVerifiedStatus
1SUMAUC0.89—Unverified
2EYMOLAUC0.83—Unverified
#ModelMetricClaimedVerifiedStatus
1Pyramid Feature AttentionMAE0.04—Unverified
2PFAN [zhao2019pyramid] (+) PRNMAE0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Pyramid Feature AttentionMAE0.03—Unverified
#ModelMetricClaimedVerifiedStatus
1InvPTmax_F184.81—Unverified
#ModelMetricClaimedVerifiedStatus
1Pyramid Feature AttentionMAE0.07—Unverified