672 citations · 1.5k across the 24 of their papers we have counts for
4 papers · 1 filter
Attentive Explanations: Justifying Decisions and Pointing to the Evidence
Dong Huk Park, Lisa Anne Hendricks, Zeynep Akata +3
Deep models are the defacto standard in visual decision models due to their impressive performance on a wide array of visual tasks. However, they are frequently seen as opaque and…
Captioning Images with Diverse Objects
Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach +3
Recent captioning models are limited in their ability to scale and describe concepts unseen in paired image-text corpora. We propose the Novel Object Captioner (NOC), a deep visual…
Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text
Subhashini Venugopalan, Lisa Anne Hendricks, Raymond Mooney +1
This paper investigates how linguistic knowledge mined from large text corpora can aid the generation of natural language descriptions of videos. Specifically, we integrate both a…
Generating Visual Explanations
Lisa Anne Hendricks, Zeynep Akata, Marcus Rohrbach +3
Clearly explaining a rationale for a classification decision to an end-user can be as important as the decision itself. Existing approaches for deep visual recognition are generall…