Abstract Vision-Language Pre-training (VLP) models have shown promising capabilities in
grounding natural language in image data, facilitating a broad range of cross-modal tasks …

Despite the remarkable accuracy of deep neural networks in object detection, they are costly
to train and scale due to supervision requirements. Particularly, learning more object …

Recent years have witnessed the resurgence of knowledge engineering which is featured
by the fast growth of knowledge graphs. However, most of existing knowledge graphs are …

Image-text matching plays a central role in bridging vision and language. Most existing
approaches only rely on the image-text instance pair to learn their representations, thereby …

Abstract Referring Video Object Segmentation (R-VOS) is a challenging task that aims to
segment an object in a video based on a linguistic expression. Most existing R-VOS …

Abstract Video Question Answering (QA) is an important task in understanding video
temporal structure. We observe that there are three unique attributes of video QA compared …

Weakly-supervised vision-language grounding aims to localize a target moment in a video
or a specific region in an image according to the given sentence query, where only video …

Visual attention not only improves the performance of image captioners, but also serves as a
visual interpretation to qualitatively measure the caption rationality and model transparency …