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Tensorflow implementation of unsupervised single image depth prediction using a convolutional neural network.
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 (Oral)
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
The main features of lmb-freiburg/flownet2 are: Optical Flow and Depth.
Projects with overlapping indexed features include: mrharicot/monodepth — Tensorflow implementation of unsupervised single image depth prediction using a convolutional neural network. nvlabs/pwc-net — PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 (Oral). tinghuiz/sfmlearner — An unsupervised learning framework for depth and ego-motion estimation from monocular videos.