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 151–200 of 364 papers

TitleStatusHype
Inducing Stronger Object Representations in Deep Visual Trackers—0
AI Marker-based Large-scale AI Literature Mining—0
Instance-Level Salient Object Segmentation—0
Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection—0
Deep Level Sets for Salient Object Detection—0
Deep Learning for Object Saliency Detection and Image Segmentation—0
Joint Attention-Guided Feature Fusion Network for Saliency Detection of Surface Defects—0
Deep Learning for Light Field Saliency Detection—0
AHMF: Adaptive Hybrid-Memory-Fusion Model for Driver Attention Prediction—0
Unsupervised CNN-based Co-Saliency Detection with Graphical Optimization—0
DeepACG: Co-Saliency Detection via Semantic-Aware Contrast Gromov-Wasserstein Distance—0
Decoding Brain Representations by Multimodal Learning of Neural Activity and Visual Features—0
Learning Background Invariance Improves Generalization and Robustness in Self-Supervised Learning on ImageNet and Beyond—0
Crowd Saliency Detection via Global Similarity Structure—0
CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection—0
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection—0
Learning Optimal Seeds for Diffusion-based Salient Object Detection—0
Co-Salient Object Detection With Uncertainty-Aware Group Exchange-Masking—0
Co-salient Object Detection Based on Deep Saliency Networks and Seed Propagation over an Integrated Graph—0
Learning to Detect Instance-level Salient Objects Using Complementary Image Labels—0
Learning to Detect Salient Objects With Image-Level Supervision—0
Learning to Explore Intrinsic Saliency for Stereoscopic Video—0
Learning to Predict Saliency on Face Images—0
AGSENet: A Robust Road Ponding Detection Method for Proactive Traffic Safety—0
WEPSAM: Weakly Pre-Learnt Saliency Model—0
Co-Saliency Detection with Co-Attention Fully Convolutional Network—0
Characterizing and Improving the Robustness of Self-Supervised Learning through Background Augmentations—0
Unsupervised learning of foreground object detection—0
Co-Saliency Detection via Mask-Guided Fully Convolutional Networks With Multi-Scale Label Smoothing—0
Light Field Saliency Detection With Dual Local Graph Learning and Reciprocative Guidance—0
Co-Saliency Detection via Looking Deep and Wide—0
Light-weighted Saliency Detection with Distinctively Lower Memory Cost and Model Size—0
Unsupervised Motor Imagery Saliency Detection Based on Self-Attention Mechanism—0
LooseCut: Interactive Image Segmentation with Loosely Bounded Boxes—0
Low-Rate Semantic Communication with Codebook-based Conditional Generative Models—0
Co-saliency Detection for RGBD Images Based on Multi-constraint Feature Matching and Cross Label Propagation—0
Unsupervised Neural Architecture for Saliency Detection: Extended Version—0
A General Framework for Saliency Detection Methods—0
Unsupervised uncertainty estimation using spatiotemporal cues in video saliency detection—0
Mitigate Domain Shift by Primary-Auxiliary Objectives Association for Generalizing Person ReID—0
Modality-Guided Subnetwork for Salient Object Detection—0
Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector—0
Contour Loss: Boundary-Aware Learning for Salient Object Segmentation—0
Multi-modal Face Pose Estimation with Multi-task Manifold Deep Learning—0
Multi-Modal Hybrid Learning and Sequential Training for RGB-T Saliency Detection—0
Multi-Scale Saliency Detection using Dictionary Learning—0
Multi-Source Uncertainty Mining for Deep Unsupervised Saliency Detection—0
What is a salient object? A dataset and a baseline model for salient object detection—0
Non-convex non-local flows for saliency detection—0
Video Saliency Detection by 3D Convolutional Neural Networks—0
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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