P2T: Pyramid Pooling Transformer for Scene Understanding

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 45; no. 11; pp. 12760 - 12771
• Main Authors: Wu, Yu-Huan, Liu, Yun, Zhan, Xin, Cheng, Ming-Ming
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: backbone network; Computational modeling; Computer networks; Convolution; efficient self-attention; Feature extraction; Image classification; Image segmentation; Network design; Object recognition; pyramid pooling; Scene analysis; scene understanding; Semantic segmentation; Semantics; Task analysis; Transformer; Transformers

Recently, the vision transformer has achieved great success by pushing the state-of-the-art of various vision tasks. One of the most challenging problems in the vision transformer is that the large sequence length of image tokens leads to high computational cost (quadratic complexity). A popular sol...