Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
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 …
Deep learning-based 3D point cloud classification: A systematic survey and outlook
In recent years, point cloud representation has become one of the research hotspots in the
field of computer vision, and has been widely used in many fields, such as autonomous …
field of computer vision, and has been widely used in many fields, such as autonomous …
Visual attention network
While originally designed for natural language processing tasks, the self-attention
mechanism has recently taken various computer vision areas by storm. However, the 2D …
mechanism has recently taken various computer vision areas by storm. However, the 2D …
Point transformer
Self-attention networks have revolutionized natural language processing and are making
impressive strides in image analysis tasks such as image classification and object detection …
impressive strides in image analysis tasks such as image classification and object detection …
Pct: Point cloud transformer
The irregular domain and lack of ordering make it challenging to design deep neural
networks for point cloud processing. This paper presents a novel framework named Point …
networks for point cloud processing. This paper presents a novel framework named Point …
Self-positioning point-based transformer for point cloud understanding
Transformers have shown superior performance on various computer vision tasks with their
capabilities to capture long-range dependencies. Despite the success, it is challenging to …
capabilities to capture long-range dependencies. Despite the success, it is challenging to …
Co-scale conv-attentional image transformers
In this paper, we present Co-scale conv-attentional image Transformers (CoaT), a
Transformer-based image classifier equipped with co-scale and conv-attentional …
Transformer-based image classifier equipped with co-scale and conv-attentional …
Rtformer: Efficient design for real-time semantic segmentation with transformer
Recently, transformer-based networks have shown impressive results in semantic
segmentation. Yet for real-time semantic segmentation, pure CNN-based approaches still …
segmentation. Yet for real-time semantic segmentation, pure CNN-based approaches still …
Pointcontrast: Unsupervised pre-training for 3d point cloud understanding
Arguably one of the top success stories of deep learning is transfer learning. The finding that
pre-training a network on a rich source set (eg, ImageNet) can help boost performance once …
pre-training a network on a rich source set (eg, ImageNet) can help boost performance once …
Se (3)-transformers: 3d roto-translation equivariant attention networks
Abstract We introduce the SE (3)-Transformer, a variant of the self-attention module for 3D
point-clouds, which is equivariant under continuous 3D roto-translations. Equivariance is …
point-clouds, which is equivariant under continuous 3D roto-translations. Equivariance is …