Attention mechanisms in computer vision: A survey
Humans can naturally and effectively find salient regions in complex scenes. Motivated by
this observation, attention mechanisms were introduced into computer vision with the aim of …
this observation, attention mechanisms were introduced into computer vision with the aim of …
The ninth NTIRE 2024 efficient super-resolution challenge report
This paper provides a comprehensive review of the NTIRE 2024 challenge focusing on
efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this …
efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this …
YOLOv5-Tassel: Detecting tassels in RGB UAV imagery with improved YOLOv5 based on transfer learning
W Liu, K Quijano, MM Crawford - IEEE Journal of Selected …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) equipped with lightweight sensors, such as RGB cameras
and LiDAR, have significant potential in precision agriculture, including object detection …
and LiDAR, have significant potential in precision agriculture, including object detection …
Attention spiking neural networks
Brain-inspired spiking neural networks (SNNs) are becoming a promising energy-efficient
alternative to traditional artificial neural networks (ANNs). However, the performance gap …
alternative to traditional artificial neural networks (ANNs). However, the performance gap …
Yolov7-sea: Object detection of maritime uav images based on improved yolov7
H Zhao, H Zhang, Y Zhao - Proceedings of the IEEE/CVF …, 2023 - openaccess.thecvf.com
Object detection algorithms play an important role in maritime search and rescue missions,
where they are designed to detect people, boats and other objects in open water. However …
where they are designed to detect people, boats and other objects in open water. However …
Contrastive learning from extremely augmented skeleton sequences for self-supervised action recognition
In recent years, self-supervised representation learning for skeleton-based action
recognition has been developed with the advance of contrastive learning methods. The …
recognition has been developed with the advance of contrastive learning methods. The …
Polarized self-attention: Towards high-quality pixel-wise mapping
We address the pixel-wise mapping problem that commonly exists in the fine-grained
computer vision tasks, such as estimating keypoint heatmaps and segmentation masks …
computer vision tasks, such as estimating keypoint heatmaps and segmentation masks …
IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approach
In recent years, colorectal cancer has become one of the most significant diseases that
endanger human health. Deep learning methods are increasingly important for the …
endanger human health. Deep learning methods are increasingly important for the …
Swift parameter-free attention network for efficient super-resolution
Abstract Single Image Super-Resolution (SISR) is a crucial task in low-level computer vision
aiming to reconstruct high-resolution images from low-resolution counterparts. Conventional …
aiming to reconstruct high-resolution images from low-resolution counterparts. Conventional …
Sparser spiking activity can be better: Feature refine-and-mask spiking neural network for event-based visual recognition
Event-based visual, a new visual paradigm with bio-inspired dynamic perception and μ s
level temporal resolution, has prominent advantages in many specific visual scenarios and …
level temporal resolution, has prominent advantages in many specific visual scenarios and …