Iuliia Kotseruba

Orcid: 0000-0002-5490-9805

According to our database1, Iuliia Kotseruba authored at least 31 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Online presence:

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Bibliography

2023
Understanding and Modeling the Effects of Task and Context on Drivers' Gaze Allocation.
CoRR, 2023

Intend-Wait-Perceive-Cross: Exploring the Effects of Perceptual Limitations on Pedestrian Decision-Making.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2023

PedFormer: Pedestrian Behavior Prediction via Cross-Modal Attention Modulation and Gated Multitask Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
Attention for Vision-Based Assistive and Automated Driving: A Review of Algorithms and Datasets.
IEEE Trans. Intell. Transp. Syst., 2022

NeurIPS 2022 Competition: Driving SMARTS.
CoRR, 2022

Intend-Wait-Cross: Towards Modeling Realistic Pedestrian Crossing Behavior.
Proceedings of the 2022 IEEE Intelligent Vehicles Symposium, 2022

2021
Industry and Academic Research in Computer Vision.
CoRR, 2021

Behavioral Research and Practical Models of Drivers' Attention.
CoRR, 2021

On the Control of Attentional Processes in Vision.
CoRR, 2021

Benchmark for Evaluating Pedestrian Action Prediction.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Driving SMARTS Competition at NeurIPS 2022: Insights and Outcome.
Proceedings of the NeurIPS 2022 Competition Track, 2021

2020
40 years of cognitive architectures: core cognitive abilities and practical applications.
Artif. Intell. Rev., 2020

Do They Want to Cross? Understanding Pedestrian Intention for Behavior Prediction.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

2019
A Possible Reason for why Data-Driven Beats Theory-Driven Computer Vision.
CoRR, 2019

Early Salient Region Selection Does Not Drive Rapid Visual Categorization.
CoRR, 2019

Why Does Data-Driven Beat Theory-Driven Computer Vision?
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshops, 2019

PIE: A Large-Scale Dataset and Models for Pedestrian Intention Estimation and Trajectory Prediction.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Pedestrian Action Anticipation using Contextual Feature Fusion in Stacked RNNs.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

Do Saliency Models Detect Odd-One-Out Targets? New Datasets and Evaluations.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018
Understanding Pedestrian Behavior in Complex Traffic Scenes.
IEEE Trans. Intell. Veh., 2018

SMILER: Saliency Model Implementation Library for Experimental Research.
CoRR, 2018

Visual Attention and its Intimate Links to Spatial Cognition.
CoRR, 2018

Towards Social Autonomous Vehicles: Understanding Pedestrian-Driver Interactions.
Proceedings of the 21st International Conference on Intelligent Transportation Systems, 2018

It's Not All About Size: On the Role of Data Properties in Pedestrian Detection.
Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

Active Fixation Control to Predict Saccade Sequences.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017
Saccade Sequence Prediction: Beyond Static Saliency Maps.
CoRR, 2017

STAR-RT: Visual attention for real-time video game playing.
CoRR, 2017

Agreeing to cross: How drivers and pedestrians communicate.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2017

Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior.
Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016
Joint Attention in Autonomous Driving (JAAD).
CoRR, 2016

A Review of 40 Years of Cognitive Architecture Research: Focus on Perception, Attention, Learning and Applications.
CoRR, 2016


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