Mind's eye: A recurrent visual representation for image caption generation
Carnegie Mellon University · Microsoft (United States)
Abstract
In this paper we explore the bi-directional mapping between images and their sentence-based descriptions. Critical to our approach is a recurrent neural network that attempts to dynamically build a visual representation of the scene as a caption is being generated or read. The representation automatically learns to remember long-term visual concepts. Our model is capable of both generating novel captions given an image, and reconstructing visual features given an image description. We evaluate our approach on several tasks. These include sentence generation, sentence retrieval and image retrieval. State-of-the-art results are shown for the task of generating novel image descriptions. When compared to human…
Citation impact
- FWCI
- 46.60
- Percentile
- 100%
- References
- 75
Authors
2Topics & keywords
- Computer science
- Artificial intelligence
- Sentence
- Representation (politics)
- Task (project management)
- Image (mathematics)
- Visualization
- Natural language processing
- Quality Education