https://github.com/shuuchen/external_attention.pytorch
Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Point Cloud Classification is a task involving the classification of unordered 3D point sets (point clouds).
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
Spherical Kernel for Efficient Graph Convolution on 3D Point Clouds
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
Frozen Transformers in Language Models Are Effective Visual Encoder Layers
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.