Satellite imageries are an important geoinformation source for different applications in the
Earth Science field. However, due to the limitation of the optic and sensor technologies and …

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 …

Abstract Convolutional Neural Networks (CNNs) are the go-to model for computer vision.
Recently, attention-based networks, such as the Vision Transformer, have also become …

We propose focal modulation networks (FocalNets in short), where self-attention (SA) is
completely replaced by a focal modulation module for modeling token interactions in vision …

Recently, Vision Transformers (ViTs) have been broadly explored in visual recognition. With
low efficiency in encoding fine-level features, the performance of ViTs is still inferior to the …

To accurately recognize plant diseases under complex natural conditions, an improved plant
disease-recognition model based on the original YOLOv5 network model was established …

While local-window self-attention performs notably in vision tasks, it suffers from limited
receptive field and weak modeling capability issues. This is mainly because it performs self …

Transformers have quickly shined in the computer vision world since the emergence of
Vision Transformers (ViTs). The dominant role of convolutional neural networks (CNNs) …

Abstract Spatial-temporal, channel-wise, and motion patterns are three complementary and
crucial types of information for video action recognition. Conventional 2D CNNs are …

For the operation and visual positioning of a banana robot, it is important to accurately
position the rachis and cut off point. However, the main factors that affect the three …