SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels

Fey, Matthias, Lenssen, Jan Eric, Weichert, Frank, Muller, Heinrich·2018·2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Cited by (452)

Items 301–400 of 452

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  78. Graph Analysis and Graph Pooling in the Spatial Domain
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  80. Deep Iterative Surface Normal Estimation
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  82. Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining
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  83. Memory-Efficient Graph Convolutional Networks for Object Classification and Detection with Event Cameras
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  84. Deep learning for action recognition in videos
    Ahmed Mazari · 2020
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  97. Peer Review #1 of "Survey on graph embeddings and their applications to machine learning problems on graphs (v0.2)"
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  98. Peer Review #3 of "Survey on graph embeddings and their applications to machine learning problems on graphs (v0.1)"
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