
Deformable Convolutional Networks
Used in [[CenterNet]]
pre: https://www.youtube.com/watch?v=HRLMSrxw2To&t=308s
解决的问题
Modeling spatial transformations is a long standing problem in computer vision
- Deformation (human pose)
- Scale
- Viewpoint variation
- Intra-class variation (不同设计的同一种物体)
Traditional approaches:
- build datasets with sufficient desired variations
- use transformation-invariant features and algorithms
架构
优势
与传统CNN拥有相同的输入输出
- regular convolution -> deformable convolution
- regular RoI pooling -> deformable RoI pooling
可以端到端训练且无需额外监督信号
直接认为是一种在物体检测方面即插即用的模块即可
Deformable Convolutional Networks
http://chen-yulin.github.io/2025/05/06/[OBS]Deep Learning-CV-Deformable Convolutional Networks/