April 2, 2024, 7:48 p.m. | Xingyi Zhou, Anurag Arnab, Shyamal Buch, Shen Yan, Austin Myers, Xuehan Xiong, Arsha Nagrani, Cordelia Schmid

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.01297v1 Announce Type: new
Abstract: An ideal model for dense video captioning -- predicting captions localized temporally in a video -- should be able to handle long input videos, predict rich, detailed textual descriptions, and be able to produce outputs before processing the entire video. Current state-of-the-art models, however, process a fixed number of downsampled frames, and make a single full prediction after seeing the whole video. We propose a streaming dense video captioning model that consists of two novel …

arxiv captioning cs.cv streaming type video

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

C003549 Data Analyst (NS) - MON 13 May

@ EMW, Inc. | Braine-l'Alleud, Wallonia, Belgium

Marketing Decision Scientist

@ Meta | Menlo Park, CA | New York City