Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Zelinsky, Gregory"'
Autor:
Mondal, Sounak, Ahn, Seoyoung, Yang, Zhibo, Balasubramanian, Niranjan, Samaras, Dimitris, Zelinsky, Gregory, Hoai, Minh
For computer systems to effectively interact with humans using spoken language, they need to understand how the words being generated affect the users' moment-by-moment attention. Our study focuses on the incremental prediction of attention as a pers
Externí odkaz:
http://arxiv.org/abs/2407.19605
Autor:
Chakraborty, Souradeep, Wei, Zijun, Kelton, Conor, Ahn, Seoyoung, Balasubramanian, Aruna, Zelinsky, Gregory J., Samaras, Dimitris
Publikováno v:
IEEE Transactions on Multimedia 25 (2022): 4478-4493
We present a model for predicting visual attention during the free viewing of graphic design documents. While existing works on this topic have aimed at predicting static saliency of graphic designs, our work is the first attempt to predict both spat
Externí odkaz:
http://arxiv.org/abs/2407.02439
Autor:
Chakraborty, Souradeep, Perez, Dana, Friedman, Paul, Sheuka, Natallia, Friedman, Constantin, Yaskiv, Oksana, Gupta, Rajarsi, Zelinsky, Gregory J., Saltz, Joel H., Samaras, Dimitris
We present a method for classifying the expertise of a pathologist based on how they allocated their attention during a cancer reading. We engage this decoding task by developing a novel method for predicting the attention of pathologists as they rea
Externí odkaz:
http://arxiv.org/abs/2403.17255
The spreading of attention has been proposed as a mechanism for how humans group features to segment objects. However, such a mechanism has not yet been implemented and tested in naturalistic images. Here, we leverage the feature maps from self-super
Externí odkaz:
http://arxiv.org/abs/2306.00294
Predicting human gaze is important in Human-Computer Interaction (HCI). However, to practically serve HCI applications, gaze prediction models must be scalable, fast, and accurate in their spatial and temporal gaze predictions. Recent scanpath predic
Externí odkaz:
http://arxiv.org/abs/2303.15274
Autor:
Yang, Zhibo, Mondal, Sounak, Ahn, Seoyoung, Xue, Ruoyu, Zelinsky, Gregory, Hoai, Minh, Samaras, Dimitris
Most models of visual attention aim at predicting either top-down or bottom-up control, as studied using different visual search and free-viewing tasks. In this paper we propose the Human Attention Transformer (HAT), a single model that predicts both
Externí odkaz:
http://arxiv.org/abs/2303.09383
Many visual phenomena suggest that humans use top-down generative or reconstructive processes to create visual percepts (e.g., imagery, object completion, pareidolia), but little is known about the role reconstruction plays in robust object recogniti
Externí odkaz:
http://arxiv.org/abs/2209.13620
The prediction of human gaze behavior is important for building human-computer interactive systems that can anticipate a user's attention. Computer vision models have been developed to predict the fixations made by people as they search for target ob
Externí odkaz:
http://arxiv.org/abs/2207.01166
Autor:
Chakraborty, Souradeep, Ma, Ke, Gupta, Rajarsi, Knudsen, Beatrice, Zelinsky, Gregory J., Saltz, Joel H., Samaras, Dimitris
We study the attention of pathologists as they examine whole-slide images (WSIs) of prostate cancer tissue using a digital microscope. To the best of our knowledge, our study is the first to report in detail how pathologists navigate WSIs of prostate
Externí odkaz:
http://arxiv.org/abs/2202.08437
The visual system processes a scene using a sequence of selective glimpses, each driven by spatial and object-based attention. These glimpses reflect what is relevant to the ongoing task and are selected through recurrent processing and recognition o
Externí odkaz:
http://arxiv.org/abs/2110.04954