3 papers
cs.MM2024
VMAS: Video-to-Music Generation via Semantic Alignment in Web Music Videos
Yan-Bo Lin, Yu Tian, Linjie Yang +2
We present a framework for learning to generate background music from video inputs. Unlike existing works that rely on symbolic musical annotations, which are limited in quantity a…
cs.CV2024
DAM: Dynamic Adapter Merging for Continual Video QA Learning
Feng Cheng, Ziyang Wang, Yi-Lin Sung +3
We present a parameter-efficient method for continual video question-answering (VidQA) learning. Our method, named DAM, uses the proposed Dynamic Adapter Merging to (i) mitigate ca…
cs.CV2024
Siamese Vision Transformers are Scalable Audio-visual Learners
Yan-Bo Lin, Gedas Bertasius
Traditional audio-visual methods rely on independent audio and visual backbones, which is costly and not scalable. In this work, we investigate using an audio-visual siamese networ…