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Scene flow is a description of real world motion in 3D that contains more information than optical flow.
Three-dimensional scene flow
Vedula, S., Baker, S., Rander, P., Collins, R., Kanade, T.: · 1999
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Real-time pattern matching using projection kernels
Hel-Or, Y., Hel-Or, H.: · 2005
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A variational method for scene flow estimation from stereo sequences
Huguet, F., Devernay, F.: · 2007
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Stereo processing by semiglobal matching and mutual information
Hirschmuller, H.: · 2008
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Large displacement optical flow: Descriptor matching in variational motion estimation
Brox, T., Malik, J.: · 2011
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Scene flow estimation by growing correspondence seeds
Čech, J., Sanchez-Riera, J., Horaud, R.: · 2011
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Are we ready for autonomous driving? The KITTI vision benchmark suite
Geiger, A., Lenz, P., Urtasun, R.: · 2012
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Multi-view scene flow estimation: A view centered variational approach
Basha, T., Moses, Y., Kiryati, N.: · 2013
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Piecewise rigid scene flow
Vogel, C., Schindler, K., Roth, S.: · 2013
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SphereFlow: 6 DoF scene flow from RGB-D pairs
Hornacek, M., Fitzgibbon, A., Rother, C.: · 2014
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Efficient joint segmentation, occlusion labeling, stereo and flow estimation
Yamaguchi, K., McAllester, D., Urtasun, R.: · 2014
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A quantitative analysis of current practices in optical flow estimation and the principles behind them
Sun, D., Roth, S., Black, M.J.: · 2014
Cited alongside, same era.
Correspondence chaining for enhanced dense 3D reconstruction
Wasenmüller, O., Krolla, B., Michielin, F., Stricker, D.: · 2014
Cited alongside, same era.
Object scene flow for autonomous vehicles
Menze, M., Geiger, A.: · 2015
Cited alongside, same era.
3D scene flow estimation with a piecewise rigid scene model
Vogel, C., Schindler, K., Roth, S.: · 2015
Cited alongside, same era.
A primal-dual framework for real-time dense RGB-D scene flow
Jaimez, M., Souiai, M., Gonzalez-Jimenez, J., Cremers, D.: · 2015
Cited alongside, same era.
Optical flow modeling and computation: A survey
Fortun, D., Bouthemy, P., Kervrann, C.: · 2015
Cited alongside, same era.
Dense wide-baseline scene flow from two handheld video cameras
Richardt, C., Kim, H., Valgaerts, L., Theobalt, C.: · 2016
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Object scene flow with temporal consistency
Neoral, M., Šochman, J.: · 2017
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Fast multi-frame stereo scene flow with motion segmentation
Taniai, T., Sinha, S.N., Sato, Y.: · 2017
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Time-of-flight sensor depth enhancement for automotive exhaust gas
Yoshida, T., Wasenmüller, O., Stricker, D.: · 2017
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CNN-based patch matching for optical flow with thresholded hinge embedding loss
Bailer, C., Varanasi, K., Stricker, D.: · 2017
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Flow Fields: Dense correspondence fields for highly accurate large displacement optical flow estimation
Bailer, C., Taetz, B., Stricker, D.: · 2015
Cited alongside, same era.
EpicFlow: Edge-preserving interpolation of correspondences for optical flow
Revaud, J., Weinzaepfel, P., Harchaoui, Z., Schmid, C.: · 2015
Cited alongside, same era.
A continuous optimization approach for efficient and accurate scene flow
Lv, Z., Beall, C., Alcantarilla, P.F., Li, F., Kira, Z., Dellaert, F.: · 2016
Cited alongside, same era.
A prediction-correction approach for real-time optical flow computation using stereo
Derome, M., Plyer, A., Sanfourche, M., Le Besnerais, G.: · 2016
Cited alongside, same era.
Bailer, C., Taetz, B., Stricker, D.: · 2017
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Bounding boxes, segmentations and object coordinates: How important is recognition for 3d scene flow estimation in autonomous driving scenarios?
Behl, A., Jafari, O.H., Mustikovela, S.K., Alhaija, H.A., Rother, C., Geiger, A.: · 2017
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Cascaded scene flow prediction using semantic segmentation
Ren, Z., Sun, D., Kautz, J., Sudderth, E.B.: · 2017
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Towards flow estimation in automotive scenarios
Schuster, R., Wasenmüller, O., Kuschk, G., Bailer, C., Stricker, D.: · 2017
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SceneFlowFields: Dense interpolation of sparse scene flow correspondences
Schuster, R., Wasenmüller, O., Kuschk, G., Bailer, C., Stricker, D.: · 2018
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