79 citations · 160 across the 18 of their papers we have counts for
11 papers · 1 filter
A deep Q-learning method for optimizing visual search strategies in backgrounds of dynamic noise
Weimin Zhou, Miguel P. Eckstein
Humans process visual information with varying resolution (foveated visual system) and explore images by orienting through eye movements the high-resolution fovea to points of inte…
FoveaTer: Foveated Transformer for Image Classification
Aditya Jonnalagadda, William Yang Wang, B. S. Manjunath +1
Many animals and humans process the visual field with a varying spatial resolution (foveated vision) and use peripheral processing to make eye movements and point the fovea to acqu…
Gaze Perception in Humans and CNN-Based Model
Nicole X. Han, William Yang Wang, Miguel P. Eckstein
Making accurate inferences about other individuals' locus of attention is essential for human social interactions and will be important for AI to effectively interact with humans.…
M3L: Language-based Video Editing via Multi-Modal Multi-Level Transformers
Tsu-Jui Fu, Xin Eric Wang, Scott T. Grafton +2
Video editing tools are widely used nowadays for digital design. Although the demand for these tools is high, the prior knowledge required makes it difficult for novices to get sta…
Diagnosing Vision-and-Language Navigation: What Really Matters
Wanrong Zhu, Yuankai Qi, Pradyumna Narayana +6
Vision-and-language navigation (VLN) is a multimodal task where an agent follows natural language instructions and navigates in visual environments. Multiple setups have been propo…
SSCR: Iterative Language-Based Image Editing via Self-Supervised Counterfactual Reasoning
Tsu-Jui Fu, Xin Eric Wang, Scott Grafton +2
Iterative Language-Based Image Editing (IL-BIE) tasks follow iterative instructions to edit images step by step. Data scarcity is a significant issue for ILBIE as it is challenging…
Counterfactual Vision-and-Language Navigation via Adversarial Path Sampling
Tsu-Jui Fu, Xin Eric Wang, Matthew Peterson +3
Vision-and-Language Navigation (VLN) is a task where agents must decide how to move through a 3D environment to reach a goal by grounding natural language instructions to the visua…
Assessment of Faster R-CNN in Man-Machine collaborative search
Arturo Deza, Amit Surana, Miguel P. Eckstein
With the advent of modern expert systems driven by deep learning that supplement human experts (e.g. radiologists, dermatologists, surveillance scanners), we analyze how and when d…
Towards Metamerism via Foveated Style Transfer
Arturo Deza, Aditya Jonnalagadda, Miguel Eckstein
The problem of is defined as finding a family of perceptually indistinguishable, yet physically different images. In this paper, we propose our NeuroFo…
Can Peripheral Representations Improve Clutter Metrics on Complex Scenes?
Arturo Deza, Miguel P. Eckstein
Previous studies have proposed image-based clutter measures that correlate with human search times and/or eye movements. However, most models do not take into account the fact that…
Object Detection Through Exploration With A Foveated Visual Field
Emre Akbas, Miguel P. Eckstein
We present a foveated object detector (FOD) as a biologically-inspired alternative to the sliding window (SW) approach which is the dominant method of search in computer vision obj…