NeurIPS 2020

Optimal visual search based on a model of target detectability in natural images

Meta Review

This paper presents a method to measure target detectability in natural images. It provides a visual search model (based on extracted features of a pre-trained CNN) to perform target detectability as a function of retinal eccentricity for human vision. Reviewers, including myself, appreciate that this paper tackles a topic that has not been well investigated in the visual search literature. The approach is well-motivated and paper is well written, and comparison with human data is a nice validation of the approach. There were issues concerning correctness of the approach, along with minor points, but the author's rebuttal has done an adequate job in addressing the concerns and I expect to see the camera ready version of the paper incorporate improvements to at will improve the clarity of the paper (esp with regards to reviewer's main concerns) using the extra page. I think this will be a nice addition to the NeurIPS2020 conference encouraging the community to look at a fresh topic, so I'm going to recommend we accept this work as a poster.