Gaze Prediction
10 papers with code • 0 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Gaze Prediction
GOO
OST
OpenEDS2020
EgoMon
Most implemented papers
Faster gaze prediction with dense networks and Fisher pruning
the-super-toys/glimpse-models
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Twitter 2018
Predicting human fixations from images has recently seen large improvements by leveraging deep representations which were pretrained for object recognition.
Predicting Gaze in Egocentric Video by Learning Task-dependent Attention Transition
hyf015/egocentric-gaze-prediction
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ECCV 2018
We present a new computational model for gaze prediction in egocentric videos by exploring patterns in temporal shift of gaze fixations (attention transition) that are dependent on egocentric manipulation tasks.
EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction
We present a new dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements.
Ecological Sampling of Gaze Shifts
Visual attention guides our gaze to relevant parts of the viewed scene, yet the moment-to-moment relocation of gaze can be different among observers even though the same locations are taken into account.
Deep Future Gaze: Gaze Anticipation on Egocentric Videos Using Adversarial Networks
Mengmi/deepfuturegaze_gan
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CVPR 2017
Through competition with discriminator, the generator progressively improves quality of the future frames and thus anticipates future gaze better.
The Story in Your Eyes: An Individual-difference-aware Model for Cross-person Gaze Estimation
bjj9/EVE_SCPT
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We propose a novel method on refining cross-person gaze prediction task with eye/face images only by explicitly modelling the person-specific differences.
GaTector: A Unified Framework for Gaze Object Prediction
CodeMonsterPHD/GaTector-A-Unified-Framework-for-Gaze-Object-Prediction
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CVPR 2022
In this paper, we build a novel framework named GaTector to tackle the gaze object prediction problem in a unified way.
L2CS-Net: Fine-Grained Gaze Estimation in Unconstrained Environments
In this paper, we propose a robust CNN-based model for predicting gaze in unconstrained settings.
Gazing at Social Interactions Between Foraging and Decision Theory
Finding the underlying principles of social attention in humans seems to be essential for the design of the interaction between natural and artificial agents.
Gazeformer: Scalable, Effective and Fast Prediction of Goal-Directed Human Attention
cvlab-stonybrook/gazeformer
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CVPR 2023
In response, we pose a new task called ZeroGaze, a new variant of zero-shot learning where gaze is predicted for never-before-searched objects, and we develop a novel model, Gazeformer, to solve the ZeroGaze problem.
