A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the part of the input it is on, then summing the results into an output.

Intuitively, a convolution allows for weight sharing - reducing the number of effective parameters - and image translation (allowing for the same feature to be detected in different parts of the input space).

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Paper Code Results Date Stars


Task Papers Share
Object Detection 55 9.15%
Semantic Segmentation 44 7.32%
Image Classification 25 4.16%
Denoising 16 2.66%
Instance Segmentation 15 2.50%
Image Generation 14 2.33%
Super-Resolution 11 1.83%
Quantization 10 1.66%
Action Recognition 9 1.50%


Component Type
🤖 No Components Found You can add them if they exist; e.g. Mask R-CNN uses RoIAlign