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Quantum Vision Transformers [PDF]
QuantumIn this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis.
El Amine Cherrat +5 more
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Rosette Trajectory MRI Reconstruction with Vision Transformers [PDF]
TomographyIntroduction: An efficient pipeline for rosette trajectory magnetic resonance imaging reconstruction is proposed, combining the inverse Fourier transform with a vision transformer (ViT) network enhanced with a convolutional layer.
Muhammed Fikret Yalcinbas +4 more
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ViTT: Vision Transformer Tracker [PDF]
Sensors, 2021 This paper presents a new model for multi-object tracking (MOT) with a transformer. MOT is a spatiotemporal correlation task among interest objects and one of the crucial technologies of multi-unmanned aerial vehicles (Multi-UAV). The transformer is a self-attentional codec architecture that has been successfully used in natural language processing and
Zhu, Xiaoning +4 more
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Applied Sciences, 2021 Person Re-Identification is an essential task in computer vision, particularly in surveillance applications. The aim is to identify a person based on an input image from surveillance photographs in various scenarios.
Muhammad Tahir, Saeed Anwar
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Prior works have proposed several strategies to reduce the computational cost of self-attention mechanism. Many of these works consider decomposing the self-attention procedure into regional and local feature extraction procedures that each incurs a much smaller computational complexity.
Ting Yao +5 more
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Multiscale Vision Transformers [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Technical ...
Fan, Haoqi +6 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 code: https://github.com/OpenNLPLab/Vicinity-Vision ...
Weixuan Sun +9 more
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Self-attention in vision transformers performs perceptual grouping, not attention
Frontiers in Computer Science, 2023 Recently, a considerable number of studies in computer vision involve deep neural architectures called vision transformers. Visual processing in these models incorporates computational models that are claimed to implement attention mechanisms. Despite an
Paria Mehrani, John K. Tsotsos
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ViTFER: Facial Emotion Recognition with Vision Transformers
Applied System Innovation, 2022 In several fields nowadays, automated emotion recognition has been shown to be a highly powerful tool. Mapping different facial expressions to their respective emotional states is the main objective of facial emotion recognition (FER).
Aayushi Chaudhari +3 more
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Multi-Manifold Attention for Vision Transformers
IEEE Access, 2023 Vision Transformers are very popular nowadays due to their state-of-the-art performance in several computer vision tasks, such as image classification and action recognition. Although their performance has been greatly enhanced through highly descriptive
Dimitrios Konstantinidis +3 more
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