CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling | Paper Citation Record

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This paper cites Deep-bcn: Deep net- works meet biased competition to create a brain-inspired model of attention control.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Deep-bcn: Deep net- works meet biased competition to create a brain-inspired model of attention control

Reference 1

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This paper cites Bruno, Eliz- abeth A.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Bruno, Eliz- abeth A

Reference 2

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This paper cites The lung image database con- sortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling The lung image database con- sortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans

Reference 3

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This paper cites Pathgan: Visual scanpath prediction with generative adversarial networks.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Pathgan: Visual scanpath prediction with generative adversarial networks

Reference 4

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This paper cites TempSAL - uncovering temporal information for deep saliency prediction.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling TempSAL - uncovering temporal information for deep saliency prediction

Reference 5

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This paper cites Reflacx, a dataset of reports and eye-tracking data for local- ization of abnormalities in chest x-rays.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Reflacx, a dataset of reports and eye-tracking data for local- ization of abnormalities in chest x-rays

Reference 6

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This paper cites Spontaneous eye movements during visual imagery reflect the content of the visual scene.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Spontaneous eye movements during visual imagery reflect the content of the visual scene

Reference 7

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This paper cites End-to- end object detection with transformers.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling End-to- end object detection with transformers

Reference 8

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This paper cites Zelinsky, and Dimitris Samaras.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Zelinsky, and Dimitris Samaras

Reference 9

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This paper cites AiR: At- tention with reasoning capability.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling AiR: At- tention with reasoning capability

Reference 10

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Observation b447c25f-5ade-4dd3-99a5-0556a681672a · outbound

This paper cites Learning from unique per- spectives: User-aware saliency modeling.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Learning from unique per- spectives: User-aware saliency modeling

Reference 11

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Observation baef2470-faff-4f29-bec3-ed203b3d86c9 · outbound

This paper cites Predicting hu- man scanpaths in visual question answering.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Predicting hu- man scanpaths in visual question answering

Reference 12

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This paper cites Beyond average: Individualized visual scanpath prediction.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Beyond average: Individualized visual scanpath prediction

Reference 13

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This paper cites Speech-to-text v2 api.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Speech-to-text v2 api

Reference 14

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This paper cites Predicting human eye fixations via an lstm-based saliency attentive model.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Predicting human eye fixations via an lstm-based saliency attentive model

Reference 15

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This paper cites Scanmatch: A novel method for comparing fixation sequences.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Scanmatch: A novel method for comparing fixation sequences

Reference 16

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This paper cites Scanpathnet: A recurrent mixture density network for scanpath prediction.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Scanpathnet: A recurrent mixture density network for scanpath prediction

Reference 17

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This paper cites It de- pends on how you look at it: Scanpath comparison in mul- tiple dimensions with multimatch, a vector-based approach.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling It de- pends on how you look at it: Scanpath comparison in mul- tiple dimensions with multimatch, a vector-based approach

Reference 18

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This paper cites Tutorial on Variational Autoencoders.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Tutorial on Variational Autoencoders

Reference 19

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This paper cites Machine-learning-based multiple abnor- mality prediction with large-scale chest computed tomogra- phy volumes.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Machine-learning-based multiple abnor- mality prediction with large-scale chest computed tomogra- phy volumes

Reference 20

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CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Unresolved cited work

Reference 21

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This paper cites Seltzer, and Jeremy M.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Seltzer, and Jeremy M

Reference 22

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This paper cites A dataset of eye movements for the children with autism spectrum disorder.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling A dataset of eye movements for the children with autism spectrum disorder

Reference 23

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This paper cites The role of extra-foveal processing in 3d imaging.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling The role of extra-foveal processing in 3d imaging

Reference 24

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This paper cites Modelling search for people in 900 scenes: A combined source model of eye guidance.Visual cognition, 17(6-7):945–978, 2009.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Modelling search for people in 900 scenes: A combined source model of eye guidance.Visual cognition, 17(6-7):945–978, 2009

Reference 25

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This paper cites Pre- dicting visual importance across graphic design types.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Pre- dicting visual importance across graphic design types

Reference 26

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This paper cites What can saliency models predict about eye movements? spatial and sequential aspects of fixations during encoding and recognition.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling What can saliency models predict about eye movements? spatial and sequential aspects of fixations during encoding and recognition

Reference 27

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This paper cites Pet: An eye-tracking dataset for animal-centric pascal object classes.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Pet: An eye-tracking dataset for animal-centric pascal object classes

Reference 28

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This paper cites Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images

Reference 29

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This paper cites Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks

Reference 30

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This paper cites SALICON: Reducing the semantic gap in saliency predic- tion by adapting deep neural networks.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling SALICON: Reducing the semantic gap in saliency predic- tion by adapting deep neural networks

Reference 31

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This paper cites The use of ma- chine learning in eye tracking studies in medical imaging: A review.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling The use of ma- chine learning in eye tracking studies in medical imaging: A review

Reference 32

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This paper cites Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

Reference 33

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This paper cites A model of saliency-based visual attention for rapid scene analysis.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling A model of saliency-based visual attention for rapid scene analysis

Reference 34

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CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Unresolved cited work

Reference 35

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CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Salicon: Saliency in context

Reference 36

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This paper cites Leiva, Hamed R.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Leiva, Hamed R

Reference 37

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This paper cites Creation and validation of a chest x-ray dataset with eye-tracking and report dictation for ai development.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Creation and validation of a chest x-ray dataset with eye-tracking and report dictation for ai development

Reference 38

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This paper cites A collaborative computer aided diagnosis (c-cad) system with eye-tracking, sparse attentional model, and deep learning.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling A collaborative computer aided diagnosis (c-cad) system with eye-tracking, sparse attentional model, and deep learning

Reference 39

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This paper cites Perspective projection-based 3d ct recon- struction from biplanar x-rays.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Perspective projection-based 3d ct recon- struction from biplanar x-rays

Reference 40

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This paper cites DeepGaze II: Reading fixations from deep features trained on object recognition.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling DeepGaze II: Reading fixations from deep features trained on object recognition

Reference 41

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CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Unresolved cited work

Reference 42

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This paper cites Methods for compar- ing scanpaths and saliency maps: Strengths and weaknesses.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Methods for compar- ing scanpaths and saliency maps: Strengths and weaknesses

Reference 43

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This paper cites Feature pyra- mid networks for object detection.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Feature pyra- mid networks for object detection

Reference 44

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This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 45

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CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Decoupled Weight Decay Regularization

Reference 46

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This paper cites Eye-Gaze-Guided Vision Transformer for Rectifying Short- cut Learning.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Eye-Gaze-Guided Vision Transformer for Rectifying Short- cut Learning

Reference 47

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This paper cites Eye- gaze Guided Multi-modal Alignment for Medical Represen- tation Learning, 2024.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Eye- gaze Guided Multi-modal Alignment for Medical Represen- tation Learning, 2024

Reference 48

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This paper cites Saccadic model of eye move- ments for free-viewing condition.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Saccadic model of eye move- ments for free-viewing condition

Reference 49

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This paper cites Gazeformer: Scalable, effective and fast prediction of goal-directed hu- man attention.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Gazeformer: Scalable, effective and fast prediction of goal-directed hu- man attention

Reference 50

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Observation 62945850-5889-4b66-b569-dd6431fa14cc · outbound

This paper cites Shedding light on ai in radiology: A systematic review and taxonomy of eye gaze-driven interpretability in deep learning.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Shedding light on ai in radiology: A systematic review and taxonomy of eye gaze-driven interpretability in deep learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:06.620847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1cf6b83e-9009-4edf-86c9-de70bd97c27b · outbound

This paper cites Training object class detectors from eye tracking data.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Training object class detectors from eye tracking data

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:06.459773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4a8e3cd6-6490-46fb-94ff-0091c8cfeae0 · outbound

This paper cites Lndetector: A flexible gaze characterisation col- laborative platform for pulmonary nodule screening.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Lndetector: A flexible gaze characterisation col- laborative platform for pulmonary nodule screening

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:06.176814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 94615f8b-d23c-4081-ac82-61cd8e096c6c · outbound

This paper cites Eye gaze guided cross-modal alignment network for radiology report generation.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Eye gaze guided cross-modal alignment network for radiology report generation

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:05.942943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f5145678-6870-4cc4-b763-56c6ee12bdfb · outbound

This paper cites I-ai: A controllable & interpretable ai system for decoding radiologists’ intense focus for accu- rate cxr diagnoses.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling I-ai: A controllable & interpretable ai system for decoding radiologists’ intense focus for accu- rate cxr diagnoses

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:05.744723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7731d124-646e-42dd-8719-ee8870a43eb3 · outbound

This paper cites Wu, Hien Nguyen, and Ngan Le.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Wu, Hien Nguyen, and Ngan Le

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:05.618095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4d7a414c-1a77-419d-b4e3-3bc58425ef3f · outbound

This paper cites Itpctrl-ai: End- to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Itpctrl-ai: End- to-end interpretable and controllable artificial intelligence by modeling radiologists’ intentions

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:05.455305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 83788f94-6875-4483-938c-29906459c62f · outbound

This paper cites Wu, Hien Nguyen, and Ngan Le.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Wu, Hien Nguyen, and Ngan Le

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:05.301178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 26c47d8e-dce9-4342-be93-76a0954de79a · outbound

This paper cites Simulating human visual sys- tem based on vision transformer.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Simulating human visual sys- tem based on vision transformer

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:05.137050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 39b27140-b69c-41f7-8e30-f5aabbf98528 · outbound

This paper cites Medical report generation through radiology images: an overview.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Medical report generation through radiology images: an overview

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:04.973956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 714a38bf-764a-421c-b823-45e24c0cb960 · outbound

This paper cites Human Attention in Fine-grained Classification.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Human Attention in Fine-grained Classification

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-06T16:49:56.218679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 771c4a3e-c49b-4be1-8ec8-b490ca3db9e0 · outbound

This paper cites Ng, and Matthew P.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Ng, and Matthew P

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:04.815152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 494da711-de5f-4b76-817e-fc8fd8afe997 · outbound

This paper cites An overview of the tesseract ocr engine.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling An overview of the tesseract ocr engine

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:04.690939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b31db0ab-7b74-469f-882b-06d3335b15c7 · outbound

This paper cites ScanDMM: A deep markov model of scan- path prediction for 360° images.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling ScanDMM: A deep markov model of scan- path prediction for 360° images

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:04.502450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 058f8ccb-c4a5-4351-b4b0-264e76063016 · outbound

This paper cites Visual scan- path prediction using IOR-ROI recurrent mixture density network.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Visual scan- path prediction using IOR-ROI recurrent mixture density network

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:04.268001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2d86618f-6b55-4730-87bf-df1417aea69c · outbound

This paper cites Artificially generated visual scanpath improves multi-label thoracic disease classification in chest x-ray images.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Artificially generated visual scanpath improves multi-label thoracic disease classification in chest x-ray images

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:03.987622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a51442bd-a5d4-486b-9027-a91743b6439b · outbound

This paper cites Interpretive Error in Radi- ology.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Interpretive Error in Radi- ology

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:03.694126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0fcac1c7-c1b6-4145-9160-e81a14032d1b · outbound

This paper cites Gazegnn: A gaze- guided graph neural network for chest x-ray classification.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Gazegnn: A gaze- guided graph neural network for chest x-ray classification

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:03.467829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9984839b-093d-4782-80cf-47562401d992 · outbound

This paper cites Laugeson, Daniel P.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Laugeson, Daniel P

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:03.187952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d4117316-e868-4fad-87ba-2c52a1cb1087 · outbound

This paper cites Follow my eye: Using gaze to supervise computer-aided diagnosis.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Follow my eye: Using gaze to supervise computer-aided diagnosis

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:02.995338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c2da3668-fb0f-4bf6-99dd-763ce473f0af · outbound

This paper cites Simulating human saccadic scanpaths on natural images.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Simulating human saccadic scanpaths on natural images

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:02.785316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 966d248c-1c5e-440e-9446-23b32b0a1c8b · outbound

This paper cites Learned region sparsity and diversity also predict visual attention.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Learned region sparsity and diversity also predict visual attention

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:02.587047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3b71ecfb-c788-4ff5-abc2-6ae261af34c9 · outbound

This paper cites an unresolved cited work.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:50:02.377501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f043f881-dd48-404c-be4e-5f67264f1cae · outbound

This paper cites Kankanhalli, and Qi Zhao.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Kankanhalli, and Qi Zhao

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:02.131193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 109f3942-d8e6-47ab-8f78-5b006945f0c8 · outbound

This paper cites Vitae: Vision transformer advanced by exploring intrinsic inductive bias.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Vitae: Vision transformer advanced by exploring intrinsic inductive bias

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:01.963145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 0201efb8-b7dc-401f-b9dd-9cee4ccddb23 · outbound

This paper cites Predicting goal-directed human attention using inverse reinforcement learning.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Predicting goal-directed human attention using inverse reinforcement learning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:01.753774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 126f6a22-c25d-4b14-a99b-596afada4166 · outbound

This paper cites Target-absent 11 human attention.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Target-absent 11 human attention

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:01.533979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b809d5ec-38d5-4ec9-a1ce-60fc123e0b84 · outbound

This paper cites Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-06T16:49:57.930125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9911886a-1305-432d-a325-e93192f79fb6 · outbound

This paper cites Unify- ing top-down and bottom-up scanpath prediction using trans- formers.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Unify- ing top-down and bottom-up scanpath prediction using trans- formers

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:01.354450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a1ee0bc7-dfa9-49da-b9a2-a871f2e621b9 · outbound

This paper cites Benchmarking gaze prediction for categori- cal visual search.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Benchmarking gaze prediction for categori- cal visual search

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:01.202013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation eda4c9a7-c507-4f76-865d-c951c9a69c4b · outbound

This paper cites Finding any waldo with zero- shot invariant and efficient visual search.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Finding any waldo with zero- shot invariant and efficient visual search

Reference 81

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T16:50:00.981852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a28b1d50-ca04-4762-b982-d073b197d9e3 · outbound

This paper cites In the original 2D version, this step divides the image into patches.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling In the original 2D version, this step divides the image into patches

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:00.848206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e6a5a86a-4149-430b-8313-d46c4d83063e · outbound

This paper cites In our 3D adapted SED, we change the step 1.a from 2D into 3D, the other steps are left as is.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling In our 3D adapted SED, we change the step 1.a from 2D into 3D, the other steps are left as is

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:00.658379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 17b06fe2-86b2-47cd-913f-80ac33569af4 · outbound

This paper cites This step is similar to the first step of SED.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling This step is similar to the first step of SED

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:00.431120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d95cebd5-c309-44c3-b110-09b1c3171f68 · outbound

This paper cites The original score function uses 2D Eu- clidean distance, which we extend to 3D Euclidean dis- tance.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling The original score function uses 2D Eu- clidean distance, which we extend to 3D Euclidean dis- tance

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:00.263875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f5443684-a686-4a34-9c44-58b15de785ab · outbound

This paper cites Higher SM scores in- dicate better matching between sequences, with an upper bound of 1.0.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Higher SM scores in- dicate better matching between sequences, with an upper bound of 1.0

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:50:00.055416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4cf7eed1-8fc1-4824-adb2-8e27a6f73ecb · outbound

This paper cites Collect all pairs(i, j) to create a similarity matrix M (i, j) between elements.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling Collect all pairs(i, j) to create a similarity matrix M (i, j) between elements

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:49:59.760425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 52f93ef7-f734-4679-904a-9c70e9267021 · outbound

This paper cites b) Direction: difference in direction (angle) between fixation vectors.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling b) Direction: difference in direction (angle) between fixation vectors

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:49:59.548849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 4fd4125a-4729-41a4-92c8-ff7969d17d79 · outbound

This paper cites b) Direction is normalized by π.

CT-ScanGaze: A Dataset and Baselines for 3D Volumetric Scanpath Modeling b) Direction is normalized by π

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:49:59.336601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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