1 code implementation • ICCV 2021 • Philipp Bomatter, Mengmi Zhang, Dimitar Karev, Spandan Madan, Claire Tseng, Gabriel Kreiman
Our model captures useful information for contextual reasoning, enabling human-level performance and better robustness in out-of-context conditions compared to baseline models across OCD and other out-of-context datasets.
1 code implementation • CVPR 2020 • Mengmi Zhang, Claire Tseng, Gabriel Kreiman
To model the role of contextual information in visual recognition, we systematically investigated ten critical properties of where, when, and how context modulates recognition, including the amount of context, context and object resolution, geometrical structure of context, context congruence, and temporal dynamics of contextual modulation.
no code implementations • 1 Feb 2019 • Mengmi Zhang, Claire Tseng, Karla Montejo, Joseph Kwon, Gabriel Kreiman
Context reasoning is critical in a wide variety of applications where current inputs need to be interpreted in the light of previous experience and knowledge.