23-06-2023 дата публикации
Номер: CN116310695A
Автор:
YAN CHENGGANG,
WU SONGHE,
ZHOU XIAOFEI,
SUN YAOQI,
ZHU ZUNJIE,
WANG SHUAI,
GAO YUHAN,
WANG HONGKUI,
YIN HAIBING,
ZHANG JIYONG,
LI ZONGPENG,
ZHAO ZHIDONG
Принадлежит:
The invention discloses a video saliency prediction method based on a gating fusion network. The method comprises the following steps: firstly, constructing the gating fusion network; the method comprises the following steps: extracting spatio-temporal features contained in a video clip through an encoder, enhancing top coding features by using a bridging module, fusing coding and decoding features by using a gating fusion module, and finally decoding the gating fusion features to predict a final saliency map. The invention provides a gating fusion module which is used for effectively fusing the multi-level characteristics of the encoder into the decoder. The module weights and encodes features along time, space and channel dimensions, so that the position of a significant object is more accurately positioned, and redundant spatio-temporal information in the features is filtered out.
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