التفاصيل البيبلوغرافية
| العنوان: |
Tencent AVS: A Holistic Ads Video Dataset for Multi-Modal Scene Segmentation |
| المؤلفون: |
Jie Jiang, Zhimin Li, Jiangfeng Xiong, Rongwei Quan, Qinglin Lu, Wei Liu |
| المصدر: |
IEEE Access, Vol 10, Pp 128959-128969 (2022) |
| بيانات النشر: |
IEEE, 2022. |
| سنة النشر: |
2022 |
| المجموعة: |
LCC:Electrical engineering. Electronics. Nuclear engineering |
| مصطلحات موضوعية: |
Scene segmentation, multi-modal learning, video understanding, Electrical engineering. Electronics. Nuclear engineering, TK1-9971 |
| الوصف: |
Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failing to describe videos in a holistic view. In addition, previous research tends to pay much attention to visual information yet ignores the multi-modal nature of videos. To fill this gap, we construct the Tencent ‘Ads Video Segmentation’ (TAVS) dataset in the ads domain to escalate multi-modal video analysis to a new level. TAVS describes videos from three independent perspectives as ‘presentation form’, ‘place’, and ‘style’, and contains rich multi-modal information such as video, audio, and text. TAVS is organized hierarchically in semantic aspects for comprehensive temporal video segmentation with three levels of categories for multi-label classification, e.g., ‘place’ - ‘working place’ - ‘office’. Therefore, TAVS is distinguished from previous temporal segmentation datasets due to its multi-modal information, holistic view of categories, and hierarchical granularities. It includes 12,000 videos, 82 classes, 33,900 segments, 121,100 shots, and 168,500 labels. Accompanied with TAVS, we also present a strong multi-modal video segmentation baseline coupled with multi-label class prediction. Extensive experiments are conducted to evaluate our proposed method as well as existing representative methods to reveal key challenges of our dataset TAVS. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2169-3536 |
| Relation: |
https://ieeexplore.ieee.org/document/9973306/; https://doaj.org/toc/2169-3536 |
| DOI: |
10.1109/ACCESS.2022.3227425 |
| URL الوصول: |
https://doaj.org/article/f57676200f544cab80f8815c960ee75e |
| رقم الانضمام: |
edsdoj.f57676200f544cab80f8815c960ee75e |
| قاعدة البيانات: |
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