Saliency Prediction
88 papers with code • 3 benchmarks • 7 datasets
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.
Benchmarks
These leaderboards are used to track progress in Saliency Prediction
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Libraries
Use these libraries to find Saliency Prediction models and implementations
SALICON
iSUN
UIEB
SUIM
MSU Video Saliency Prediction
Salient-KITTI
Latest papers with no code
Shifting Focus with HCEye: Exploring the Dynamics of Visual Highlighting and Cognitive Load on User Attention and Saliency Prediction
Visual highlighting can guide user attention in complex interfaces.
Separated Attention: An Improved Cycle GAN Based Under Water Image Enhancement Method
In this paper we have present an improved Cycle GAN based model for under water image enhancement.
How is Visual Attention Influenced by Text Guidance? Database and Model
Finally, considering the effect of text descriptions on visual attention, while most existing saliency models ignore this impact, we further propose a text-guided saliency (TGSal) prediction model, which extracts and integrates both image features and text features to predict the image saliency under various text-description conditions.
SalFoM: Dynamic Saliency Prediction with Video Foundation Models
Recent advancements in video saliency prediction (VSP) have shown promising performance compared to the human visual system, whose emulation is the primary goal of VSP.
GreenSaliency: A Lightweight and Efficient Image Saliency Detection Method
Image saliency detection is crucial in understanding human gaze patterns from visual stimuli.
Selective Attention-based Modulation for Continual Learning
We present SAM, a biologically-plausible selective attention-driven modulation approach to enhance classification models in a continual learning setting.
DiffGaze: A Diffusion Model for Continuous Gaze Sequence Generation on 360° Images
We present DiffGaze, a novel method for generating realistic and diverse continuous human gaze sequences on 360{\deg} images based on a conditional score-based denoising diffusion model.
Learning User Embeddings from Human Gaze for Personalised Saliency Prediction
At the core of our method is a Siamese convolutional neural encoder that learns the user embeddings by contrasting the image and personal saliency map pairs of different users.
A Modified Word Saliency-Based Adversarial Attack on Text Classification Models
This paper introduces a novel adversarial attack method targeting text classification models, termed the Modified Word Saliency-based Adversarial At-tack (MWSAA).
DiffSal: Joint Audio and Video Learning for Diffusion Saliency Prediction
Audio-visual saliency prediction can draw support from diverse modality complements, but further performance enhancement is still challenged by customized architectures as well as task-specific loss functions.
