An integrated computational model of visual search combining eccentricity, bottom-up and top-down cues. India Institute of Technology Kanpur (2021).
Read his thesis here
Read his NeurIPS 2021 paper related to his thesis work. Visual search asymmetry: DeepNets and Humans share similar inherent biases. Gupta et al, NeurIPS 2021
Congratulations to Mengmi Zhang in her successful defense of her Ph.D. thesis!
Mengmi Zhang. Computational Models of Bottom-up and Top-down Attention. National University of Singapore (2019).
See also Zhang’s recent publications:
Gupta SK, Zhang M, Wu CC, Wolfe JM, Kreiman G (2021). Visual Search Asymmetry: Deep Nets and Humans Share Similar Inherent Biases. NeurIPS arXiv 2106.02953 PDF
Zhang M, Tseng C, Kreiman G. (2020) Putting visual object recognition in context. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit (CVPR) 12982-12991 PDF
Zhang M, Kreiman G (2021). Beauty is in the eye of the machine. Nature Human Behavior 5:1-2 PDF
Bomatter P, Zhang M, Karev D, Madan S, Tseng C, Kreiman G (2021). When Pigs Fly: Contextual Reasoning in Synthetic and Natural Scenes. International Conference on Computer Vision (ICCV) arXiv 2104.02215 PDF
Zhang M, Feng J, Ma KT, Lim JH, Zhao Q, Kreiman G. (2018) Finding any Waldo: zero-shot invariant and efficient visual search. Nature Communications, 9:3730. PDF