Deep Learning has implemented a wide range of applications and has become increasingly
popular in recent years. The goal of multimodal deep learning (MMDL) is to create models …

Deep Learning has implemented a wide range of applications and has become increasingly
popular in recent years. The goal of multimodal deep learning is to create models that can …

Automated generation of 3D human motions from text is a challenging problem. The
generated motions are expected to be sufficiently diverse to explore the text-grounded …

The canonical approach to video captioning dictates a caption generation model to learn
from offline-extracted dense video features. These feature extractors usually operate on …

Dense video captioning aims to generate multiple associated captions with their temporal
locations from the video. Previous methods follow a sophisticated" localize-then-describe" …

Taking full advantage of the information from both vision and language is critical for the
video captioning task. Existing models lack adequate visual representation due to the …

Generating multi-sentence descriptions for video is considered to be the most complex task
in computer vision and natural language understanding due to the intricate nature of video …

Video captioning is a challenging task that requires a deep understanding of visual scenes.
State-of-the-art methods generate captions using either scene-level or object-level …

Recently, chest X-ray report generation, which aims to automatically generate descriptions
of given chest X-ray images, has received growing research interests. The key challenge of …

This paper considers a video caption generating network referred to as Semantic Grouping
Network (SGN) that attempts (1) to group video frames with discriminating word phrases of …