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20242026
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cs.CV2026

Gaze-to-text Generation: Beyond Categorical Decoding of Human Attention

Sounak Mondal, Dimitris Samaras, Gregory Zelinsky +1

We introduce a novel learning problem: decoding gaze into natural language descriptions of human goals across diverse visual tasks. Unlike prior work, which frames gaze decoding as…

cs.CV2026

Pathologist Attention-Aligned Report Generation for Prostate Histopathology

Ruoyu Xue, Suryakant Singh, Souradeep Chakraborty +12

The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracted from whole-slide images (W…

cs.CV2026

Human-like Object Grouping in Self-supervised Vision Transformers

Hossein Adeli, Seoyoung Ahn, Andrew Luo +3

Vision foundation models trained with self-supervised objectives achieve strong performance across diverse tasks and exhibit emergent object segmentation properties. However, their…

cs.CV2026

Generating metamers of human scene understanding

Ritik Raina, Abe Leite, Alexandros Graikos +3

Human vision combines low-resolution "gist" information from the visual periphery with sparse but high-resolution information from fixated locations to construct a coherent underst…

cs.CV2025

Personalized Image Descriptions from Attention Sequences

Ruoyu Xue, Hieu Le, Jingyi Xu +5

People can view the same image differently: they focus on different regions, objects, and details in varying orders and describe them in distinct linguistic styles. This leads to s…

cs.CV2025

Few-shot Personalized Scanpath Prediction

Ruoyu Xue, Jingyi Xu, Sounak Mondal +4

A personalized model for scanpath prediction provides insights into the visual preferences and attention patterns of individual subjects. However, existing methods for training sca…