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 …
Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
Segnext: Rethinking convolutional attention design for semantic segmentation
We present SegNeXt, a simple convolutional network architecture for semantic
segmentation. Recent transformer-based models have dominated the field of se-mantic …
segmentation. Recent transformer-based models have dominated the field of se-mantic …
Hornet: Efficient high-order spatial interactions with recursive gated convolutions
Recent progress in vision Transformers exhibits great success in various tasks driven by the
new spatial modeling mechanism based on dot-product self-attention. In this paper, we …
new spatial modeling mechanism based on dot-product self-attention. In this paper, we …
Large selective kernel network for remote sensing object detection
Recent research on remote sensing object detection has largely focused on improving the
representation of oriented bounding boxes but has overlooked the unique prior knowledge …
representation of oriented bounding boxes but has overlooked the unique prior knowledge …
Davit: Dual attention vision transformers
In this work, we introduce Dual Attention Vision Transformers (DaViT), a simple yet effective
vision transformer architecture that is able to capture global context while maintaining …
vision transformer architecture that is able to capture global context while maintaining …
Vitaev2: Vision transformer advanced by exploring inductive bias for image recognition and beyond
Vision transformers have shown great potential in various computer vision tasks owing to
their strong capability to model long-range dependency using the self-attention mechanism …
their strong capability to model long-range dependency using the self-attention mechanism …
Inceptionnext: When inception meets convnext
Inspired by the long-range modeling ability of ViTs large-kernel convolutions are widely
studied and adopted recently to enlarge the receptive field and improve model performance …
studied and adopted recently to enlarge the receptive field and improve model performance …
Fast vision transformers with hilo attention
Abstract Vision Transformers (ViTs) have triggered the most recent and significant
breakthroughs in computer vision. Their efficient designs are mostly guided by the indirect …
breakthroughs in computer vision. Their efficient designs are mostly guided by the indirect …
NTIRE 2023 challenge on efficient super-resolution: Methods and results
This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …