Results 11 to 20 of about 170,334 (258)
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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A Survey on Vision Transformer [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism. Thanks to its strong representation capabilities, researchers are looking at ways to apply transformer to computer vision tasks.
Kai Han +12 more
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Reversible Vision Transformers
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 We present Reversible Vision Transformers, a memory efficient architecture design for visual recognition. By decoupling the GPU memory requirement from the depth of the model, Reversible Vision Transformers enable scaling up architectures with efficient memory usage.
Mangalam, Karttikeya +6 more
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Building Extraction With Vision Transformer [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Submitted to ...
Libo Wang +3 more
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Vision Transformer with Progressive Sampling [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Accepted to ICCV ...
Yue, X +6 more
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Semi-supervised Vision Transformers
, 2022 We study the training of Vision Transformers for semi-supervised image classification. Transformers have recently demonstrated impressive performance on a multitude of supervised learning tasks. Surprisingly, we show Vision Transformers perform significantly worse than Convolutional Neural Networks when only a small set of labeled data is available ...
Zejia Weng +4 more
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Machine Learning and Knowledge Extraction, 2023 This study introduces an optimal topology of vision transformers for real-time video action recognition in a cloud-based solution. Although model performance is a key criterion for real-time video analysis use cases, inference latency plays a more ...
Saman Sarraf, Milton Kabia
doaj +1 more source
Measuring miniature eye movements by means of a SQUID magnetometer [PDF]
, 1982 A new technique to measure small eye movements is reported. The precise recording of human eye movements is necessary for research on visual fatigue induced by visual display units.1 So far all methods used have disadvantages: especially those which are ...
Breukink, E.W. +4 more
core +4 more sources