arXiv:2409.13538
First Place Solution to the Multiple-choice Video QA Track of The Second Perception Test Challenge
원문 초록
In this report, we present our first-place solution to the Multiple-choice Video Question Answering (QA) track of The Second Perception Test Challenge. This competition posed a complex video understanding task, requiring models to accurately comprehend and answer questions about video content. To address this challenge, we leveraged the powerful QwenVL2 (7B) model and fine-tune it on the provided training set. Additionally, we employed model ensemble strategies and Test Time Augmentation to boost performance. Through continuous optimization, our approach achieved a Top-1 Accuracy of 0.7647 on the leaderboard.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
VUDG: A Dataset for Video Understanding Domain Generalization
LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs
video-SALMONN 2: Captioning-Enhanced Audio-Visual Large Language Models
EgoVLM: Policy Optimization for Egocentric Video Understanding
How Far Can Off-the-Shelf Multimodal Large Language Models Go in Online Episodic Memory Question Answering?
VersaVid-R1: A Versatile Video Understanding and Reasoning Model from Question Answering to Captioning Tasks
토론
이 논문과 연결된 포럼 글이 아직 없습니다.