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