Fusion of multimodal embeddings for ad-hoc video search

• Main Authors: FRANCIS, Danny, NGUYEN, Phuong Anh, HUET, Benoit, NGO, Chong-wah
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Deep learning; Multimedia; Multimodal embeddings; Multimodal fusion; Video search; Databases and Information Systems; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6462; https://ink.library.smu.edu.sg/context/sis_research/article/7465/viewcontent/Francis_Fusion_of_Multimodal_Embeddings_for_Ad_Hoc_Video_Search_ICCVW_2019_paper.pdf
• Institution: Singapore Management University

The challenge of Ad-Hoc Video Search (AVS) originates from free-form (i.e., no pre-defined vocabulary) and freestyle (i.e., natural language) query description. Bridging the semantic gap between AVS queries and videos becomes highly difficult as evidenced from the low retrieval accuracy of AVS bench...