Deep learning techniques have led to remarkable breakthroughs in the field of object
detection and have spawned a lot of scene-understanding tasks in recent years. Scene …

Existing research of video understanding still struggles to achieve in-depth comprehension
and reasoning in complex videos, primarily due to the under-exploration of two key …

Different objects in the same scene are more or less related to each other, but only a limited
number of these relationships are noteworthy. Inspired by Detection Transformer, which …

Transformer models have shown great success handling long-range interactions, making
them a promising tool for modeling video. However, they lack inductive biases and scale …

Text-to-image synthesis (T2I) aims to generate photo-realistic images which are
semantically consistent with the text descriptions. Existing methods are usually built upon …

As one of the core video semantic understanding tasks, Video Semantic Role Labeling
(VidSRL) aims to detect the salient events from given videos, by recognizing the predict …

Recent advances in face forgery techniques produce nearly visually untraceable deepfake
videos, which could be leveraged with malicious intentions. As a result, researchers have …

Stock price forecasting has remained an extremely challenging problem for many decades
due to the high volatility of the stock market. Recent efforts have been devoted to modeling …

Video-based visual relation detection tasks such as video scene graph generation play
important roles in fine-grained video understanding. However current video visual relation …

Cardiac cine magnetic resonance imaging (MRI) reconstruction is challenging due to spatial
and temporal resolution trade-offs. Temporal correlation in cardiac cine MRI is informative …