While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides,
they mostly fall prey to the limitation of only input-side multimodal understanding, without the …

Generating an image/video caption has always been a fundamental problem of Artificial
Intelligence, which is usually performed using the potential of Deep Learning Methods …

Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

Existing video captioning approaches typically require to first sample video frames from a
decoded video and then conduct a subsequent process (eg, feature extraction and/or …

Pre-trained models have demonstrated considerable performance, especially in enhancing
cross-modal understanding between videos and text. However, fine-tuning them at scale …

Multi-modal knowledge graph completion (MMKGC) aims to automatically discover the
unobserved factual knowledge from a given multi-modal knowledge graph by collaboratively …

Video captioning is a multi-modal task across computer vision and natural language
processing. Previous methods generally follow two paradigms, ie template-based and …

Spatio-temporal video grounding (or STVG) task aims at locating a spatio-temporal tube for
a specific instance given a text query. Despite advancements current methods easily suffer …

Recent advancements in video-language understanding have been established on the
foundation of image-text models, resulting in promising outcomes due to the shared …

Video Transformers have become the prevalent solution for various video downstream tasks
with superior expressive power and flexibility. However these video transformers suffer from …