Separating the “chirp” from the “chat”: self-supervised visual grounding of sound and language

التفاصيل البيبلوغرافية
العنوان: Separating the “chirp” from the “chat”: self-supervised visual grounding of sound and language
المؤلفون: Hamilton, M, Zisserman, A, Hershey, JR, Freeman, WT
بيانات النشر: IEEE
سنة النشر: 2024
المجموعة: Oxford University Research Archive (ORA)
الوصف: We present DenseAV, a novel dual encoder grounding architecture that learns high-resolution, semantically meaningful, and audio-visual aligned features solely through watching videos. We show that DenseAV can discover the “meaning” of words and the “location” of sounds without explicit localization supervision. Furthermore, it automatically discovers and distinguishes between these two types of associations without supervision. We show that DenseAV's localization abilities arise from a new multi-head feature aggregation operator that directly compares dense image and audio representations for contrastive learning. In contrast, many other systems that learn “global” audio and video representations cannot localize words and sound. Finally, we contribute two new datasets to improve the evaluation of AV representations through speech and sound prompted semantic segmentation. On these and other datasets we show DenseAV dramatically outperforms the prior art on speech and sound prompted semantic segmentation. DenseAV outperforms the current state-of-the-art, ImageBind, on cross-modal retrieval using fewer than half of the parameters. Project Page: https://aka.ms/denseav
نوع الوثيقة: conference object
اللغة: English
Relation: https://doi.org/10.1109/cvpr52733.2024.01246
DOI: 10.1109/cvpr52733.2024.01246
الاتاحة: https://doi.org/10.1109/cvpr52733.2024.01246
https://ora.ox.ac.uk/objects/uuid:2d4a16f0-f8b7-43b1-ab5a-ee996814d2d0
Rights: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.5419239A
قاعدة البيانات: BASE
الوصف
DOI:10.1109/cvpr52733.2024.01246