I am thinking about using implicit models to do implicit information aggregation.
Say you pre-train a network to predict (r, g, b) = net(x, y). Then you fine-tune it to do something else, let's say, predict if a pixel is object or stuff.
Do you think the implicit model could encode in net_backbone(x, y) information about its context, like a CNN? I mean, does it just learn punctually or does it collect context information?
Say you pre-train a network to predict (r, g, b) = net(x, y). Then you fine-tune it to do something else, let's say, predict if a pixel is object or stuff.
Do you think the implicit model could encode in net_backbone(x, y) information about its context, like a CNN? I mean, does it just learn punctually or does it collect context information?