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Found 3 papers, 3 papers with code
Whole Brain Segmentation with Full Volume Neural Network
To address these issues, we propose to adopt a full volume framework, which feeds the full volume brain image into the segmentation network and directly outputs the segmentation result for the whole brain volume.
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks
To overcome this challenge, we propose a generic new approach that bridges the gap between image-conditional and recent modulated unconditional generative architectures via co-modulation of both conditional and stochastic style representations.
Ranked #3 on
Image Inpainting
on FFHQ 512 x 512
MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask
In this paper, we propose an asymmetric occlusion-aware feature matching module, which can learn a rough occlusion mask that filters useless (occluded) areas immediately after feature warping without any explicit supervision.
Ranked #2 on
Optical Flow Estimation
on KITTI 2012
