Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
This work addresses the challenge of image captioning for applications in accessibility, search, and human-computer interaction, representing a novel integration of attention mechanisms rather than an incremental improvement.
The paper tackles the problem of automatically generating descriptive captions for images by introducing an attention-based neural model that learns to focus on salient visual regions while producing corresponding words. The model achieves state-of-the-art performance on benchmark datasets Flickr8k, Flickr30k, and MS COCO.
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. We describe how we can train this model in a deterministic manner using standard backpropagation techniques and stochastically by maximizing a variational lower bound. We also show through visualization how the model is able to automatically learn to fix its gaze on salient objects while generating the corresponding words in the output sequence. We validate the use of attention with state-of-the-art performance on three benchmark datasets: Flickr8k, Flickr30k and MS COCO.