Involution: Inverting the Inherence of Convolution for Visual Recognition (Research Paper Explained)

#involution #computervision #attention Convolutional Neural Networks (CNNs) have dominated computer vision for almost a decade by applying two fundamental principles: Spatial agnosticism and channel-specific computations. Involution aims to invert these principles and presents a spatial-specific computation, which is also channel-agnostic. The resulting Involution Operator and RedNet architecture are a compromise between classic Convolutions and the newer Local Self-Attention architectures and perform favorably in terms of computation accuracy tradeoff when compared to either. OUTLINE: 0:00 - Intro & Overview 3:00 - Principles of Convolution 10:50 - Towards spatial-specific computations 17:00 - The Involution Operator 20:00 - Comparison to Self-Attention 25:15 - Experimental Results 30:30 - Comments & Conclusion Paper: Code: Abstract: Convolution has been the core ingredient of modern neural networks, triggering the surge of deep learni