A feedforward mechanism for human-like contour integration
Fig 3
Impact of receptive field size and progression on contour integration in feedforward models.
(A) left: shows the receptive field progression over the layers (blue lines), relative to the standard Alexnet model (gray); right: shows the size of the receptive fields of units in the 5th Convolutional block the final stage of the backbone before the fully-connected layers. (B) Top-1 object recognition accuracy on the ImageNet validation set for PinholeNet models with varying receptive field sizes (blue bars), as well as the standard Alexnet model (gray bar). (C) Contour detection accuracy for readout from the 5th convolutional layer (left), and the 2nd fully-connected layer (right) in PinholeNets (blue bars) and the standard Alexnet model (grey bar) on the held-out test set. The error bars denote the 95% confidence intervals for readout accuracy.