329 citations · 492 across the 7 of their papers we have counts for
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Deep Learning the City : Quantifying Urban Perception At A Global Scale
Abhimanyu Dubey, Nikhil Naik, Devi Parikh +2
Computer vision methods that quantify the perception of urban environment are increasingly being used to study the relationship between a city's physical appearance and the behavio…
Towards Transparent AI Systems: Interpreting Visual Question Answering Models
Yash Goyal, Akrit Mohapatra, Devi Parikh +1
Deep neural networks have shown striking progress and obtained state-of-the-art results in many AI research fields in the recent years. However, it is often unsatisfying to not kno…
Image Specificity
Mainak Jas, Devi Parikh
For some images, descriptions written by multiple people are consistent with each other. But for other images, descriptions across people vary considerably. In other words, some im…
Collecting Image Description Datasets using Crowdsourcing
Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh
We describe our two new datasets with images described by humans. Both the datasets were collected using Amazon Mechanical Turk, a crowdsourcing platform. The two datasets contain…
CIDEr: Consensus-based Image Description Evaluation
Ramakrishna Vedantam, C. Lawrence Zitnick, Devi Parikh
Automatically describing an image with a sentence is a long-standing challenge in computer vision and natural language processing. Due to recent progress in object detection, attri…
Human-Machine CRFs for Identifying Bottlenecks in Holistic Scene Understanding
Roozbeh Mottaghi, Sanja Fidler, Alan Yuille +2
Recent trends in image understanding have pushed for holistic scene understanding models that jointly reason about various tasks such as object detection, scene recognition, shape…