Pupil Dilation
5 papers with code • 0 benchmarks • 0 datasets
Phenomenon on which the human iris reacts to illumination changes and drugs; thus, changing the aperture of the pupil.
Benchmarks
These leaderboards are used to track progress in Pupil Dilation
Most implemented papers
The Sensorium competition on predicting large-scale mouse primary visual cortex activity
The neural underpinning of the biological visual system is challenging to study experimentally, in particular as the neuronal activity becomes increasingly nonlinear with respect to visual input.
Stimulus domain transfer in recurrent models for large scale cortical population prediction on video
sinzlab/Sinz2018_NIPS
•
•
NeurIPS 2018
However, in many cases this approach requires that the model is able to generalize to stimulus statistics that it was not trained on, such as band-limited noise and other parameterized stimuli.
A flow-based latent state generative model of neural population responses to natural images
sinzlab/bashiri-et-al-2021
•
•
NeurIPS 2021
We present a joint deep neural system identification model for two major sources of neural variability: stimulus-driven and stimulus-conditioned fluctuations.
DeformIrisNet: An Identity-Preserving Model of Iris Texture Deformation
Nonlinear iris texture deformations due to pupil size variations are one of the main factors responsible for within-class variance of genuine comparison scores in iris recognition.
Artificial Pupil Dilation for Data Augmentation in Iris Semantic Segmentation
dpbenalcazar/ArtificialDilation
•
•
2022 IEEE Sixth Ecuador Technical Chapters Meeting (ETCM) 2022
The results indicate that our data augmentation method can improve segmentation accuracy up to 15% for images with high pupil dilation, which creates a more reliable iris recognition pipeline, even under extreme dilation.
