Over the past few decades, numerous studies have focused on identifying and recognizing
human actions using machine learning and computer vision techniques. Video-based …

Modeling disease progression is crucial for improving the quality and efficacy of clinical
diagnosis and prognosis, but it is often hindered by a lack of longitudinal medical image …

Current video generation models excel at generating short clips but still struggle with
creating multi-shot, movie-like videos. Existing models trained on large-scale data on the …

With recent advances of AIGC, video generation have gained a surge of research interest in
both academia and industry (eg, Sora). However, it remains a challenge to produce …

Large Language Models (LLMs) have transformed numerous domains by providing
advanced capabilities in natural language understanding, generation, and reasoning …

Video paragraph captioning aims to describe a video that contains multiple events with a
paragraph of generated coherent sentences. Such a captioning task is full of challenges …

Class incremental learning (CIL) strives to emulate the human cognitive process of
continuously learning and adapting to new tasks while retaining knowledge from past …

Semantic communications (SEMCOM) is a novel communication model that exploits neural
networks or deep learning techniques to convey the semantics of the data and contextual …

Video generation has achieved impressive quality, but it still suffers from artifacts such as
temporal inconsistency and violation of physical laws. Leveraging 3D scenes can …

We consider the problem of efficiently representing casually captured monocular videos in a
spatially-and temporally-coherent manner. While existing approaches predominantly rely on …