Video understanding using multimodal deep learning
<p>Our experience of the world is multimodal, however deep learning networks have been traditionally designed for and trained on unimodal inputs such as images, audio segments or text. In this thesis we develop strategies to exploit multimodal information (in the form of vision, text, speech a...
Κύριος συγγραφέας: | Nagrani, A |
---|---|
Άλλοι συγγραφείς: | Zisserman, A |
Μορφή: | Thesis |
Γλώσσα: | English |
Έκδοση: |
2020
|
Θέματα: |
Παρόμοια τεκμήρια
-
Sign language understanding using multimodal learning
ανά: Momeni, L
Έκδοση: (2024) -
Understanding Multimodal Popularity Prediction of Social Media Videos With Self-Attention
ανά: Adam Bielski, κ.ά.
Έκδοση: (2018-01-01) -
End-to-end learning, and audio-visual human-centric video understanding
ανά: Brown, A
Έκδοση: (2022) -
Holistic image understanding with deep learning and dense random fields
ανά: Zheng, S
Έκδοση: (2016) -
Learning with multimodal self-supervision
ανά: Chen, H
Έκδοση: (2021)