SOTAVerified

Scanpath prediction

Learning to Predict Sequences of Human Fixations.

Papers

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Showing 11–20 of 34 papers

TitleStatusHype
Gravitational Laws of Focus of AttentionCode0
Variational Laws of Visual Attention for Dynamic ScenesCode0
Pathformer3D: A 3D Scanpath Transformer for 360° ImagesCode0
SalyPath360: Saliency and Scanpath Prediction Framework for Omnidirectional Images—0
SALYPATH: A Deep-Based Architecture for visual attention prediction—0
Scanpath Prediction in Panoramic Videos via Expected Code Length Minimization—0
Scanpath Prediction on Information Visualisations—0
Self Supervised Scanpath Prediction Framework for Painting Images—0
State-of-the-Art in Human Scanpath Prediction—0
Unified Dynamic Scanpath Predictors Outperform Individually Trained Neural Models—0
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All datasetsCapMIT1003Coutrot Dataset 1FixaTons

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1NevaClipSBTDE0.38—Unverified
2G-EymolSBTDE0.34—Unverified
#ModelMetricClaimedVerifiedStatus
1G-EYMOLScaled time-delay embeddings0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1G-EYMOLScaled time-delay embeddings0.85—Unverified