SOTAVerified

Saliency Prediction

A saliency map is a model that predicts eye fixations on a visual scene. Saliency prediction is informed by the human visual attention mechanism and predicts the possibility of the human eyes to stay in a certain position in the scene.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 126–150 of 268 papers

TitleStatusHype
Social Saliency Prediction—0
Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency—0
Spatio-Temporal Saliency Networks for Dynamic Saliency Prediction—0
Statistically Consistent Saliency Estimation—0
Supersaliency: A Novel Pipeline for Predicting Smooth Pursuit-Based Attention Improves Generalizability of Video Saliency—0
SUSiNet: See, Understand and Summarize it—0
Task-driven Webpage Saliency—0
Task Specific Visual Saliency Prediction with Memory Augmented Conditional Generative Adversarial Networks—0
Teaching AI to Teach: Leveraging Limited Human Salience Data Into Unlimited Saliency-Based Training—0
Text-Audio-Visual-conditioned Diffusion Model for Video Saliency Prediction—0
The Effect of Distortions on the Prediction of Visual Attention—0
Toward Improving the Evaluation of Visual Attention Models: a Crowdsourcing Approach—0
Training Deep Networks to be Spatially Sensitive—0
Transformer-based Video Saliency Prediction with High Temporal Dimension Decoding—0
Tumor Saliency Estimation for Breast Ultrasound Images via Breast Anatomy Modeling—0
Ubernet: Training a Universal Convolutional Neural Network for Low-, Mid-, and High-Level Vision Using Diverse Datasets and Limited Memory—0
Ultrasound Image Representation Learning by Modeling Sonographer Visual Attention—0
Understanding Low- and High-Level Contributions to Fixation Prediction—0
Noise Perturbation for Saliency Prediction with Psychophysical Synthetic Images—0
Unified Dynamic Scanpath Predictors Outperform Individually Trained Neural Models—0
UniST: Towards Unifying Saliency Transformer for Video Saliency Prediction and Detection—0
Unsupervised Video Object Segmentation using Motion Saliency-Guided Spatio-Temporal Propagation—0
ViDaS Video Depth-aware Saliency Network—0
Video Saliency Detection by 3D Convolutional Neural Networks—0
Visual Attention driven by Convolutional Features—0
Show:102550
← PrevPage 6 of 11Next →
All datasetsSALECISALICONMIT300CAT2000

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1TransalnetKL0.87—Unverified
2TempSALKL0.71—Unverified
3SSwin transformerKL0.65—Unverified
4ECT-SALKL0.58—Unverified
5SUMKL0.47—Unverified
#ModelMetricClaimedVerifiedStatus
1SUMAUC0.88—Unverified
2SalNAS-XL + Self-KDAUC0.87—Unverified
3TempSALAUC0.87—Unverified
4MDS-ViTNetAUC0.87—Unverified
5TranSalNetAUC0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1SUMAUC-Judd0.91—Unverified
2TranSalNetAUC-Judd0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1SUMKL0.27—Unverified