17 citations · 133 across the 50 of their papers we have counts for
3 papers · 1 filter
Localizing Occluders with Compositional Convolutional Networks
Adam Kortylewski, Qing Liu, Huiyu Wang +2
Compositional convolutional networks are generative compositional models of neural network features, that achieve state of the art results when classifying partially occluded objec…
TDAPNet: Prototype Network with Recurrent Top-Down Attention for Robust Object Classification under Partial Occlusion
Mingqing Xiao, Adam Kortylewski, Ruihai Wu +3
Despite deep convolutional neural networks' great success in object classification, it suffers from severe generalization performance drop under occlusion due to the inconsistency…
Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion
Adam Kortylewski, Qing Liu, Huiyu Wang +2
Deep convolutional neural networks (DCNNs) are powerful models that yield impressive results at object classification. However, recent work has shown that they do not generalize we…