Search Results for author: Ryan Kiros

Found 11 papers, 8 papers with code

Order-Embeddings of Images and Language

2 code implementations19 Nov 2015 Ivan Vendrov, Ryan Kiros, Sanja Fidler, Raquel Urtasun

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

Cross-Modal Retrieval Image Captioning +2

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

3 code implementations ICCV 2015 Yukun Zhu, Ryan Kiros, Richard Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, Sanja Fidler

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 how these states evolve through a story.

Descriptive Sentence +2

Skip-Thought Vectors

16 code implementations NeurIPS 2015 Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Antonio Torralba, Raquel Urtasun, Sanja Fidler

The end result is an off-the-shelf encoder that can produce highly generic sentence representations that are robust and perform well in practice.

Sentence

Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

87 code implementations10 Feb 2015 Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard Zemel, Yoshua Bengio

Inspired by recent work in machine translation and object detection, we introduce an attention based model that automatically learns to describe the content of images.

Image Captioning Translation

Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models

3 code implementations10 Nov 2014 Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel

Inspired by recent advances in multimodal learning and machine translation, we introduce an encoder-decoder pipeline that learns (a): a multimodal joint embedding space with images and text and (b): a novel language model for decoding distributed representations from our space.

Language Modelling Machine Translation +2

A Multiplicative Model for Learning Distributed Text-Based Attribute Representations

no code implementations NeurIPS 2014 Ryan Kiros, Richard S. Zemel, Ruslan Salakhutdinov

In this paper we propose a general framework for learning distributed representations of attributes: characteristics of text whose representations can be jointly learned with word embeddings.

Attribute Cross-Lingual Document Classification +8

Training Neural Networks with Stochastic Hessian-Free Optimization

no code implementations16 Jan 2013 Ryan Kiros

Hessian-free (HF) optimization has been successfully used for training deep autoencoders and recurrent networks.

General Classification

Deep Representations and Codes for Image Auto-Annotation

no code implementations NeurIPS 2012 Ryan Kiros, Csaba Szepesvári

The task of assigning a set of relevant tags to an image is challenging due to the size and variability of tag vocabularies.

feature selection TAG

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