deeplearningopticflowestimation

•Optic Flow

•Brightness Constancy Constraints

•Aperture Problem

•Regularization and Smoothness Constraints

•Lucas-Kanade algorithm

•Focus of Expansion (FOE)

•Discrete Optimization for Optical Flow

•Large Displacement Optical Flow: Descriptor Matching

•EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow

•Optical Flow with Piecewise Parametric Model

•SPM-BP: Sped-up PatchMatch Belief Propagation

•Coarse-to-Fine PatchMatch for Large Optical Flow

•Flow Fields: Correspondence Fields for Optical Flow

•Full Flow: Optic Flow Estimate By Global Optimization over Regular Grids

•DeepFlow: Large displ. optical flow with deep matching

•FlowNet: Learning Optical Flow with ConvNets

•Deep Discrete Flow

•Optical Flow Estimation using a Spatial Pyramid Network

•A Large Dataset to Train ConvNets for Disparity, Optical Flow, and Scene Flow Estimation

•DeMoN: Depth/Motion Net for Learning Mono- Stereo

•Unsupervised Learning of Depth/Ego-Motion from Video

•Appendix A: A Database and Evaluation for Optical Flow

•Appendix B: Secret of Optic Flow Estimation

•Appendix C: Deep Learning and optimization theory