Paper Citation Record · LEDGER

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs

As of 9 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 1 inbound Pith citation observation for arXiv:2511.09867.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2511.09867 v2

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Pith citing papers itemized under the disclosed page cap.

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Outbound references

Observation d5d62d6f-50d2-42aa-8eb2-48a0a816329f · outbound

This paper cites Advances in eye tracking technology: theory, algorithms, and applications.Computational intelligence and neuroscience, 2016:7831469, 2016.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Advances in eye tracking technology: theory, algorithms, and applications.Computational intelligence and neuroscience, 2016:7831469, 2016

Reference 1

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Observation cb51d5ec-1626-42b5-b37e-377f90c45d42 · outbound

This paper cites Eye-tracking in ar/vr: A technological review and future directions.IEEE Open Journal on Immersive Displays, 2024.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye-tracking in ar/vr: A technological review and future directions.IEEE Open Journal on Immersive Displays, 2024

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.309418Z

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Observation a93d4b80-78b0-45d0-b87f-6122db922cbe · outbound

This paper cites Gazebase, a large-scale, multi-stimulus, longitudinal eye movement dataset.Scientific Data, 8(1):184, 2021.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Gazebase, a large-scale, multi-stimulus, longitudinal eye movement dataset.Scientific Data, 8(1):184, 2021

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.374146Z

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Observation 563c4d6e-99c3-452f-9bbe-3d98cab4b009 · outbound

This paper cites The promise of eye-tracking methodology in organizational research: A taxonomy, review, and future avenues.Organizational Research Methods, 22(2):590–617, 2019.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs The promise of eye-tracking methodology in organizational research: A taxonomy, review, and future avenues.Organizational Research Methods, 22(2):590–617, 2019

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Observation 74284fa7-6faa-4c9f-bf38-6fc2b652c18c · outbound

This paper cites Eye-tracking based classification of Mandarin Chinese readers with and without dyslexia using neural sequence models.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye-tracking based classification of Mandarin Chinese readers with and without dyslexia using neural sequence models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.450155Z

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Observation 88ec8dae-3578-45fb-a4f0-89d3817cddc8 · outbound

This paper cites Eye-tracking based autism spectrum disorder diagnosis using chaotic butterfly optimization with deep learning model.Computers, Materials & Continua, 76(2), 2023.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye-tracking based autism spectrum disorder diagnosis using chaotic butterfly optimization with deep learning model.Computers, Materials & Continua, 76(2), 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.455691Z

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Observation cf7d485d-609e-45a2-81c2-7a2e05279a79 · outbound

This paper cites Eye know you too: Toward viable end-to-end eye movement biometrics for user authentication.IEEE Transactions on Information Forensics and Security, 17:3151–3164, 2022.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye know you too: Toward viable end-to-end eye movement biometrics for user authentication.IEEE Transactions on Information Forensics and Security, 17:3151–3164, 2022

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.461719Z

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Observation d71c0f01-154a-4e3a-923d-8a9182c147fa · outbound

This paper cites Gaze authentication: Factors influencing authentication performance.arXiv preprint arXiv:2509.10969, 2025.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Gaze authentication: Factors influencing authentication performance.arXiv preprint arXiv:2509.10969, 2025

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.466653Z

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Observation 4d6b3cf0-767a-467d-812f-a182f54978b7 · outbound

This paper cites Person identification using ocular biometrics with liveness detection, July 14 2015.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Person identification using ocular biometrics with liveness detection, July 14 2015

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.473224Z

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Observation 1cdc6c97-759c-4793-b215-275bd397a949 · outbound

This paper cites Iris print attack detection using eye movement signals.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Iris print attack detection using eye movement signals

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.478293Z

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Observation f3925c24-9701-418e-9aa5-19798c2ee1a5 · outbound

This paper cites Towards foveated rendering for gaze-tracked virtual reality.ACM Transactions On Graphics (TOG), 35 (6):1–12, 2016.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Towards foveated rendering for gaze-tracked virtual reality.ACM Transactions On Graphics (TOG), 35 (6):1–12, 2016

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.484423Z

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Observation b612b30b-45a5-46b9-b8e2-b182fe48a02a · outbound

This paper cites Improving user experience of eye tracking-based interaction: Introspecting and adapting interfaces.ACM Transactions on Computer-Human Interaction (TOCHI), 26(6):1–46, 2019.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Improving user experience of eye tracking-based interaction: Introspecting and adapting interfaces.ACM Transactions on Computer-Human Interaction (TOCHI), 26(6):1–46, 2019

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Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.489211Z

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Observation 0e3603ee-ad45-4f4d-ad53-acb61881ac18 · outbound

This paper cites Brockmole, and Sidney K.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Brockmole, and Sidney K

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.494908Z

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Observation c2a55cc3-7554-4586-a81e-6a3340c8fd55 · outbound

This paper cites A new comprehensive eye-tracking test battery concurrently evaluating the pupil labs glasses and the eyelink 1000.PeerJ, 7:e7086, 2019.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs A new comprehensive eye-tracking test battery concurrently evaluating the pupil labs glasses and the eyelink 1000.PeerJ, 7:e7086, 2019

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.500638Z

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Observation 632579fc-d4ae-4f61-a99c-23a2caf9c93e · outbound

This paper cites Biometric verification via complex eye movements: The effects of environment and stimulus.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Biometric verification via complex eye movements: The effects of environment and stimulus

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.507219Z

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Observation 99eab054-5422-4c9c-bf66-fd2de688b592 · outbound

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Unresolved cited work

Reference 16

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Observation 22f4f55b-dfa0-4fba-bdbc-00fea0347f15 · outbound

This paper cites Supreyes: Super resolutin for eyes using implicit neural representation learning.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Supreyes: Super resolutin for eyes using implicit neural representation learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.516510Z

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Observation 2d651dd6-2fbd-4609-bc29-2c6bc186e891 · outbound

This paper cites A survey of advances in vision-based vehicle re-identification.Computer Vision and Image Understanding, 182:50–63, 2019.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs A survey of advances in vision-based vehicle re-identification.Computer Vision and Image Understanding, 182:50–63, 2019

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Observation 673e5727-9b6e-48cf-958a-957c098f3058 · outbound

This paper cites Privacy-aware eye tracking using differential privacy.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Privacy-aware eye tracking using differential privacy

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Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.526185Z

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Observation 42502c30-7f3f-4bd1-82a9-afa9f0ff81b4 · outbound

This paper cites Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.Computer Methods and Programs in Biomedicine, 260: 108571, 2025.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.Computer Methods and Programs in Biomedicine, 260: 108571, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.530689Z

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Observation 303cac78-3bc8-4e97-b8a6-4b12f8c3e393 · outbound

This paper cites Eyes alive.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eyes alive

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Observation aa3775c8-8c5e-4f11-b734-711327d77182 · outbound

This paper cites Eyesyn: Psychology-inspired eye movement synthesis for gaze-based activity recognition.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eyesyn: Psychology-inspired eye movement synthesis for gaze-based activity recognition

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Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.540695Z

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This paper cites Generative adversarial networks.Communications of the ACM, 63(11):139–144, 2020.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Generative adversarial networks.Communications of the ACM, 63(11):139–144, 2020

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Observation 4d21baec-158f-4679-b2fd-e3a53d86275c · outbound

This paper cites Sp-eyegan: Generating synthetic eye movement data with generative adversarial networks.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Sp-eyegan: Generating synthetic eye movement data with generative adversarial networks

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Observation 5c51f420-52e6-4610-bee0-5b1ed9c104eb · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

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Observation 42c2e42f-05ef-426f-9582-d6a477373c2e · outbound

This paper cites DiffEyeSyn: Diffusion-based User-specific Eye Movement Synthesis.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs DiffEyeSyn: Diffusion-based User-specific Eye Movement Synthesis

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This paper cites Determining which sine wave frequencies correspond to signal and which correspond to noise in eye-tracking time-series.Journal of Eye Movement Research, 14(3):16, 2021.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Determining which sine wave frequencies correspond to signal and which correspond to noise in eye-tracking time-series.Journal of Eye Movement Research, 14(3):16, 2021

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Observation 605d0c0e-d8ce-458a-82af-7df3900127f9 · outbound

This paper cites Evaluation of eye tracking signal quality for virtual reality applications: A case study in the meta quest pro.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Evaluation of eye tracking signal quality for virtual reality applications: A case study in the meta quest pro

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This paper cites Modeling physiologically plausible eye rotations.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Modeling physiologically plausible eye rotations

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye movement synthesis

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This paper cites Natural eye motion synthesis by modeling gaze-head coupling.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Natural eye motion synthesis by modeling gaze-head coupling

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Observation fe3c7d21-8790-49ee-ba8a-3824826a0428 · outbound

This paper cites Rendering of eyes for eye-shape registration and gaze estimation.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Rendering of eyes for eye-shape registration and gaze estimation

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Observation 9496aaed-dd69-463b-951a-e6572bcaf04f · outbound

This paper cites Live speech driven head-and-eye motion generators.IEEE transactions on visualization and computer graphics, 18(11):1902–1914, 2012.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Live speech driven head-and-eye motion generators.IEEE transactions on visualization and computer graphics, 18(11):1902–1914, 2012

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye movement velocity and gaze data generator for evaluation, robustness testing and assess of eye tracking software and visualization tools

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eye movement simulation and detector creation to reduce laborious parameter adjustments

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This paper cites Eyecatch: Simulating visuomotor coordination for object interception.ACM Transactions on Graphics (TOG), 31(4):1–10, 2012.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eyecatch: Simulating visuomotor coordination for object interception.ACM Transactions on Graphics (TOG), 31(4):1–10, 2012

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs An introduction to the kalman filter

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Observation 9523959a-2d10-44f1-8f7e-7530a1f57349 · outbound

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Automatic scanpath generation with deep recurrent neural networks

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Pathgan: Visual scanpath prediction with generative adversarial networks

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Observation daf8f368-584d-4a73-9139-b4fd477922a0 · outbound

This paper cites Eyegan: Gaze-preserving, mask-mediated eye image synthesis.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Eyegan: Gaze-preserving, mask-mediated eye image synthesis

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Fully convolutional neural networks for raw eye tracking data segmentation, generation, and reconstruction

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Next-generation deep learning based on simulators and synthetic data.Trends in cognitive sciences, 26(2):174–187, 2022

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Hpcgen: Hierarchical k-means clustering and level based principal components for scan path genaration

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Improved denoising diffusion probabilistic models

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Diffgaze: A diffusion model for modelling fine-grained human gaze behaviour on 360° images.ACM Transactions on Interactive Intelligent Systems, 2025

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Adding conditional control to text-to-image diffusion models

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs DiffWave: A Versatile Diffusion Model for Audio Synthesis

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Observation 0a1b4bbe-7d63-4f5c-a6e5-33716d5319a8 · outbound

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Smoothing and differentiation of data by simplified least squares procedures.Analytical chemistry, 36(8):1627–1639, 1964

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Identifying fixations and saccades in eye-tracking protocols

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Observation 6d13e648-c7c3-4622-8519-87c0f1acbb7d · outbound

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Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Adam: A Method for Stochastic Optimization

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Resolution: unresolved; no resolver link, observed 2026-08-03T22:36:33.670187Z

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Observation 71111d4a-1c71-4d07-81d5-32684c8a4e7d · outbound

This paper cites Evaluating the Data Quality of Eye Tracking Signals from a Virtual Reality System: Case Study using SMI's Eye-Tracking HTC Vive.

Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs Evaluating the Data Quality of Eye Tracking Signals from a Virtual Reality System: Case Study using SMI's Eye-Tracking HTC Vive

Reference 51

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Pith citing papers

Observation 028e9353-76c2-4568-9986-c04041a4133c · inbound

Privatization of Synthetic Gaze: Attenuating State Signatures in Diffusion-Generated Eye Movements cites this paper.

Privatization of Synthetic Gaze: Attenuating State Signatures in Diffusion-Generated Eye Movements Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GANs

Reference 17

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