activity
20122015
most citedShow, Attend and Tell: Neural Image Caption Generation with Visual Attention

7.4k citations · 11.1k across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2015★ 87 cited

Order-Embeddings of Images and Language

Ivan Vendrov, Ryan Kiros, Sanja Fidler +1

Hypernymy, textual entailment, and image captioning can be seen as special cases of a single visual-semantic hierarchy over words, sentences, and images. In this paper we advocate…

cs.LG2015★ 354 cited

Action Recognition using Visual Attention

Shikhar Sharma, Ryan Kiros, Ruslan Salakhutdinov

We propose a soft attention based model for the task of action recognition in videos. We use multi-layered Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) units…

cs.CL2015★ 722 cited

Skip-Thought Vectors

Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov +4

We describe an approach for unsupervised learning of a generic, distributed sentence encoder. Using the continuity of text from books, we train an encoder-decoder model that tries…

cs.CV2015★ 297 cited

Aligning Books and Movies: Towards Story-like Visual Explanations by Watching Movies and Reading Books

Yukun Zhu, Ryan Kiros, Richard Zemel +4

Books are a rich source of both fine-grained information, how a character, an object or a scene looks like, as well as high-level semantics, what someone is thinking, feeling and h…

cs.LG2015★ 387 cited

Exploring Models and Data for Image Question Answering

Mengye Ren, Ryan Kiros, Richard Zemel

This work aims to address the problem of image-based question-answering (QA) with new models and datasets. In our work, we propose to use neural networks and visual semantic embedd…

stat.ML2015★ 438 cited

Scalable Bayesian Optimization Using Deep Neural Networks

Jasper Snoek, Oren Rippel, Kevin Swersky +6

Bayesian optimization is an effective methodology for the global optimization of functions with expensive evaluations. It relies on querying a distribution over functions defined b…