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End-to-End Semantic Video Transformer for Zero-Shot Action Recognition

End-to-End Semantic Video Transformer for Zero-Shot Action Recognition

10 March 2022
Keval Doshi
Yasin Yılmaz
    ViT
ArXivPDFHTML

Papers citing "End-to-End Semantic Video Transformer for Zero-Shot Action Recognition"

7 / 7 papers shown
Title
Can we predict the Most Replayed data of video streaming platforms?
Can we predict the Most Replayed data of video streaming platforms?
Alessandro Duico
Ombretta Strafforello
J. C. V. Gemert
8
1
0
12 Sep 2023
Tell me what you see: A zero-shot action recognition method based on
  natural language descriptions
Tell me what you see: A zero-shot action recognition method based on natural language descriptions
Valter Estevam
Rayson Laroca
David Menotti
Hélio Pedrini
17
13
0
18 Dec 2021
VidTr: Video Transformer Without Convolutions
VidTr: Video Transformer Without Convolutions
Yanyi Zhang
Xinyu Li
Chunhui Liu
Bing Shuai
Yi Zhu
Biagio Brattoli
Hao Chen
I. Marsic
Joseph Tighe
ViT
136
193
0
23 Apr 2021
Is Space-Time Attention All You Need for Video Understanding?
Is Space-Time Attention All You Need for Video Understanding?
Gedas Bertasius
Heng Wang
Lorenzo Torresani
ViT
278
1,939
0
09 Feb 2021
Rethinking Zero-shot Video Classification: End-to-end Training for
  Realistic Applications
Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications
Biagio Brattoli
Joseph Tighe
Fedor Zhdanov
Pietro Perona
Krzysztof Chalupka
VLM
129
127
0
03 Mar 2020
Learning Attributes Equals Multi-Source Domain Generalization
Learning Attributes Equals Multi-Source Domain Generalization
Chuang Gan
Tianbao Yang
Boqing Gong
OOD
150
197
0
03 May 2016
Efficient Estimation of Word Representations in Vector Space
Efficient Estimation of Word Representations in Vector Space
Tomáš Mikolov
Kai Chen
G. Corrado
J. Dean
3DV
228
31,150
0
16 Jan 2013
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