Multimodal Summarization
| Thesis title in Czech: | Multimodální Sumarizace |
|---|---|
| Thesis title in English: | Multimodal Summarization |
| Key words: | sumarizace|textová sumarizace|modelování vidění a jazyka|multimodální data |
| English key words: | summarization|text summarization|vision-language modeling|multimodal data |
| Academic year of topic announcement: | 2020/2021 |
| Thesis type: | dissertation |
| Thesis language: | angličtina |
| Department: | Institute of Formal and Applied Linguistics (32-UFAL) |
| Supervisor: | doc. RNDr. Pavel Pecina, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 08.09.2020 |
| Date of assignment: | 08.09.2020 |
| Confirmed by Study dept. on: | 05.10.2020 |
| Date and time of defence: | 27.09.2024 13:00 |
| Date of electronic submission: | 15.07.2024 |
| Date of submission of printed version: | 15.07.2024 |
| Date of proceeded defence: | 27.09.2024 |
| Opponents: | Dr. Mohamed Hasanuzzaman |
| prof. Dr. Adam Jatowt | |
| Guidelines |
| Multimodal summarization is the task of automatic construction of summaries of information resources in multimodal formats such as texts, images, videos and audios. The goal of the thesis is to study the recent advances in the area of multimodal summarization, explore possible data sets for training and evaluation, and advance the state of the art by proposing and evaluating new methods and applications. |
| References |
| Ian Goodfellow, Yoshua Bengio and Aaron Courville. Deep Learning. MIT Press. 2016
Zhu, Junnan et al. “MSMO: Multimodal Summarization with Multimodal Output.” EMNLP 2018 Junnan Zhu, Yu Zhou, Jiajun Zhang, Haoran Li, Chengqing Zong, Changliang Li: Multimodal Summarization with Guidance of Multimodal Reference. AAAI 2020: |