HIGHLIGHTS
- who: Heeju Im and Yong-Suk Choi from the Department of Computer Science and Engineering, Hanyang University, Seoul, Korea have published the research work: UAT: Universal Attention Transformer for Video Captioning, in the Journal: Sensors 2022, 22, 4817. of /2022/
- what: The complexity of the model is further increased when multiple CNNs are used. The authors propose the full transformer structure that uses an end-to-end learning method for captioning to overcome this problem. The authors design a universal encoder attraction (UEA) that uses all encoder layer outputs and performs self-attention on the . . .
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