Results 11 to 20 of about 24,887 (267)

A Review of Transformer-Based Approaches for Image Captioning

Applied Sciences, 2023
Visual understanding is a research area that bridges the gap between computer vision and natural language processing. Image captioning is a visual understanding task in which natural language descriptions of images are automatically generated using ...
Oscar Ondeng, Heywood Ouma, Peter Akuon
doaj   +1 more source

Vicinity Vision Transformer

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
code: https://github.com/OpenNLPLab/Vicinity-Vision ...
Weixuan Sun, Zhen Qin 0003, Hui Deng, Jianyuan Wang, Yi Zhang 0137, Kaihao Zhang, Nick Barnes, Stan Birchfield, Lingpeng Kong, Yiran Zhong   +9 more
openaire   +3 more sources

STHarDNet: Swin Transformer with HarDNet for MRI Segmentation

Applied Sciences, 2022
In magnetic resonance imaging (MRI) segmentation, conventional approaches utilize U-Net models with encoder–decoder structures, segmentation models using vision transformers, or models that combine a vision transformer with an encoder–decoder model ...
Yeonghyeon Gu, Zhegao Piao, Seong Joon Yoo   +2 more
doaj   +1 more source

Building Extraction With Vision Transformer [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2022
Submitted to ...
Libo Wang, Shenghui Fang, Xiaoliang Meng, Rui Li 0036   +3 more
openaire   +2 more sources

Peripheral Vision Transformer

Advances in Neural Information Processing Systems 35, 2022
Human vision possesses a special type of visual processing systems called peripheral vision. Partitioning the entire visual field into multiple contour regions based on the distance to the center of our gaze, the peripheral vision provides us the ability to perceive various visual features at different regions.
Juhong Min, Yucheng Zhao, Chong Luo 0001, Minsu Cho   +3 more
openaire   +3 more sources

Vision Transformer with Progressive Sampling [PDF]

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021
Accepted to ICCV ...
Xiaoyu Yue, Shuyang Sun, Zhanghui Kuang, Meng Wei 0007, Philip H. S. Torr, Wayne Zhang 0001, Dahua Lin   +6 more
openaire   +3 more sources

Convolutional Neural Networks or Vision Transformers: Who Will Win the Race for Action Recognitions in Visual Data?

Sensors, 2023
Understanding actions in videos remains a significant challenge in computer vision, which has been the subject of several pieces of research in the last decades.
Oumaima Moutik, Hiba Sekkat, Smail Tigani, Abdellah Chehri, Rachid Saadane, Taha Ait Tchakoucht, Anand Paul   +6 more
doaj   +1 more source

Transformer-based ripeness segmentation for tomatoes

Smart Agricultural Technology, 2023
With the recent development of computer vision technology, various computer vision techniques have been applied to agriculture. Recently, the Transformer network has been introduced to image recognition, which allows a different approach to extracting ...
Risa Shinoda, Hirokatsu Kataoka, Kensho Hara, Ryozo Noguchi   +3 more
doaj   +1 more source

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.
Karttikeya Mangalam, Haoqi Fan 0001, Yanghao Li, Chao-Yuan Wu, Bo Xiong, Christoph Feichtenhofer, Jitendra Malik   +6 more
openaire   +2 more sources

Transformer architectures for computer vision: A comprehensive review and future research directions [PDF]

EPJ Web of Conferences
Long-range dependencies and contextual relationships in videos were captured by using Convolutional Neural Networks (CNNs) in past. Recently the use of Transformers is started for capturing the long-range dependencies and contextual relationships in ...
Ugile Tukaram, Uke Nilesh
doaj   +1 more source