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Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video
  Retrieval

Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval

3 December 2021
Fan Hu
Aozhu Chen
Ziyu Wang
Fangming Zhou
Jianfeng Dong
Xirong Li
ArXivPDFHTML

Papers citing "Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval"

6 / 6 papers shown
Title
Koala: Key frame-conditioned long video-LLM
Koala: Key frame-conditioned long video-LLM
Reuben Tan
Ximeng Sun
Ping Hu
Jui-hsien Wang
Hanieh Deilamsalehy
Bryan A. Plummer
Bryan C. Russell
Kate Saenko
38
35
0
05 Apr 2024
(Un)likelihood Training for Interpretable Embedding
(Un)likelihood Training for Interpretable Embedding
Jiaxin Wu
Chong-Wah Ngo
W. Chan
Zhijian Hou
12
2
0
01 Jul 2022
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip
  Retrieval
CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval
Huaishao Luo
Lei Ji
Ming Zhong
Yang Chen
Wen Lei
Nan Duan
Tianrui Li
CLIP
VLM
303
771
0
18 Apr 2021
A Straightforward Framework For Video Retrieval Using CLIP
A Straightforward Framework For Video Retrieval Using CLIP
Jesús Andrés Portillo-Quintero
J. C. Ortíz-Bayliss
Hugo Terashima-Marín
CLIP
302
116
0
24 Feb 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
Multi-modal Transformer for Video Retrieval
Multi-modal Transformer for Video Retrieval
Valentin Gabeur
Chen Sun
Alahari Karteek
Cordelia Schmid
ViT
401
594
0
21 Jul 2020
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