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Pyramid Self-attention for Semantic Segmentation
2021Self-attention is vital in computer vision since it is the building block of Transformer and can model long-range context for visual recognition. However, computing pairwise self-attention between all pixels for dense prediction tasks (e.g., semantic segmentation) costs high computation.
Jiyang Qi +4 more
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Fast Self-Attentive Multimodal Retrieval
2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 2018Multimodal bidirectional retrieval is a very challenging task that consists of semantically aligning two distinct modalities such as images and textual descriptions, allowing the retrieval of content from one of the modalities given the other. The goal is to find a common semantic space for both modalities in order to discover the correspondences ...
Jonatas Wehrmann +3 more
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Relation-mining self-attention network for skeleton-based human action recognition
Pattern Recognition, 2023Yanli Ji +2 more
exaly
Self-attention neural architecture search for semantic image segmentation
Knowledge-Based Systems, 2022Junyu Dong, Guosheng Hu
exaly
Relation constraint self-attention for image captioning
Neurocomputing, 2022Junzhong Ji +2 more
exaly
A Dual Self-Attention mechanism for vehicle re-Identification
Pattern Recognition, 2023Wenqian Zhu +2 more
exaly
Cascaded feature fusion with multi-level self-attention mechanism for object detection
Pattern Recognition, 2023exaly
MHSA-Net: Multihead Self-Attention Network for Occluded Person Re-Identification
IEEE Transactions on Neural Networks and Learning Systems, 2023Hongchen Tan, , Xiuping Liu
exaly