2.3k citations · 3.3k across the 4 of their papers we have counts for
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2 papers · 1 filter
cs.CV2016★ 48 cited
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Eddy Ilg, Nikolaus Mayer, Tonmoy Saikia +3
The FlowNet demonstrated that optical flow estimation can be cast as a learning problem. However, the state of the art with regard to the quality of the flow has still been defined…
cs.CV2016★ 772 cited
DeMoN: Depth and Motion Network for Learning Monocular Stereo
Benjamin Ummenhofer, Huizhong Zhou, Jonas Uhrig +4
In this paper we formulate structure from motion as a learning problem. We train a convolutional network end-to-end to compute depth and camera motion from successive, unconstraine…