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Learn to Understand Movies.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Learn to Understand Movies./
作者:	Huang, Qingqiu.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	208 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:	Dissertations Abstracts International83-03B.
標題:	Film studies. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28735885
ISBN:	9798535514536

Learn to Understand Movies.
Huang, Qingqiu.

Learn to Understand Movies. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 208 p.

Source: Dissertations Abstracts International, Volume: 83-03, Section: B.

Thesis (Ph.D.)--Hong Kong University of Science and Technology (Hong Kong), 2020.

Movie, where characters would face various situations and perform various behaviors in various scenarios, is a reflection of our real world. It teaches us a lot such as the stories that took place in the past, the culture and custom of a country or a place, the reaction and interaction of humans in different situations, etc. Therefore, to understand movies is to understand our world. It goes not only for humans, but also for an artificial intelligence system. We believe that movie understanding is a good arena for high-level machine intelligence, considering its high complexity and close relation to the real world. What's more, compared to web images and short videos, the hundreds of thousands of movies in history containing rich content and multi-modality information become better nutrition for the data-hungry deep models.However, despite the remarkable advances in visual understanding, how to understand a story-based long video with artistic style remains an open question. In this thesis, we aim to facilitate this topic by exploiting movie understanding with learning methods.To be specific, we first introduce a holistic dataset for movie understanding named MovieNet and multiple important topics in movie analysis. Then we try to begin with a simple problem, i.e. tag classification, where we take advantage of the trailers to learn visual models that can be applied to movies. And as a human-centric video, characters play an important role in movie analysis, especially for story-based video understanding. So in the following parts, we studied how to recognize the cast in movies effectively and efficiently, including how to train a face model without labels, how to unify different visual cues, how to use temporal features, and how to take advantage of multi-modal information with memory.

ISBN: 9798535514536Subjects--Topical Terms:

2122736
Film studies.
Subjects--Index Terms:

Motion pictures

Learn to Understand Movies.
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