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 #1 on Image Inpainting on FFHQ 512 x 512
Self-driving cars need to understand 3D scenes efficiently and accurately in order to drive safely.
Ranked #3 on 3D Semantic Segmentation on SemanticKITTI
Furthermore, with only 20% training data, we can match the top performance on CIFAR-10 and CIFAR-100.
Ranked #1 on Image Generation on CIFAR-10 (20% data)
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 #1 on Optical Flow Estimation on KITTI 2015
We present recursive cascaded networks, a general architecture that enables learning deep cascades, for deformable image registration.
3D medical image registration is of great clinical importance.