984 citations · 1k across the 9 of their papers we have counts for
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Reinforcing an Image Caption Generator Using Off-Line Human Feedback
Paul Hongsuck Seo, Piyush Sharma, Tomer Levinboim +2
Human ratings are currently the most accurate way to assess the quality of an image captioning model, yet most often the only used outcome of an expensive human rating evaluation i…
Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering
Soravit Changpinyo, Bo Pang, Piyush Sharma +1
Object detection plays an important role in current solutions to vision and language tasks like image captioning and visual question answering. However, popular models like Faster…
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman +3
Increasing model size when pretraining natural language representations often results in improved performance on downstream tasks. However, at some point further model increases be…
Neural Naturalist: Generating Fine-Grained Image Comparisons
Maxwell Forbes, Christine Kaeser-Chen, Piyush Sharma +1
We introduce the new Birds-to-Words dataset of 41k sentences describing fine-grained differences between photographs of birds. The language collected is highly detailed, while rema…
Quality Estimation for Image Captions Based on Large-scale Human Evaluations
Tomer Levinboim, Ashish V. Thapliyal, Piyush Sharma +1
Automatic image captioning has improved significantly over the last few years, but the problem is far from being solved, with state of the art models still often producing low qual…
Informative Image Captioning with External Sources of Information
Sanqiang Zhao, Piyush Sharma, Tomer Levinboim +1
An image caption should fluently present the essential information in a given image, including informative, fine-grained entity mentions and the manner in which these entities inte…