With the exponential surge in diverse multimodal data, traditional unimodal retrieval
methods struggle to meet the needs of users seeking access to data across various …

Abstract Scene Graph Generation, which generally follows a regular encoder-decoder
pipeline, aims to first encode the visual contents within the given image and then parse them …

Transformer achieves remarkable successes in understanding 1 and 2-dimensional signals
(eg, NLP and Image Content Understanding). As a potential alternative to convolutional …

Almost all previous text-to-video retrieval works assume that videos are pre-trimmed with
short durations. However, in practice, videos are generally untrimmed containing much …

Fashion Compatibility Modeling (FCM) is a new yet challenging task, which aims to
automatically access the matching degree among a set of complementary items. Most of …

This paper aims for the task of text-to-video retrieval, where given a query in the form of a
natural-language sentence, it is asked to retrieve videos which are semantically relevant to …

Current methods for text-to-video retrieval (T2VR) are trained and tested on video-captioning
oriented datasets such as MSVD, MSR-VTT and VATEX. A key property of these datasets is …

Visual Question Answering aims to answer the free-form natural language question based
on the visual clues in a given image. It is a difficult problem as it requires understanding the …

This article studies the multimedia problem of temporal sentence grounding (TSG), which
aims to accurately determine the specific video segment in an untrimmed video according to …

Abstract 3D dense captioning is a recently-proposed novel task, where point clouds contain
more geometric information than the 2D counterpart. However, it is also more challenging …