SGANVO uses stacked GAN layers with recurrent connections to estimate depth and ego-motion unsupervisedly from images, reporting better or comparable results on the KITTI dataset.
”PWC-Net: CNNs for optical flow using pyramid, warping, and cost volume.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
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SGANVO: Unsupervised Deep Visual Odometry and Depth Estimation with Stacked Generative Adversarial Networks
SGANVO uses stacked GAN layers with recurrent connections to estimate depth and ego-motion unsupervisedly from images, reporting better or comparable results on the KITTI dataset.