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Elsevier DOI
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IEEE DOI
1006
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Motion
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Elsevier DOI
1505
Scene Flow
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Wang, Y.C.[Yu-Cheng],
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IEEE DOI
1608
BibRef
Earlier:
Completed Dense Scene Flow in RGB-D Space,
BD3DCV14(191-205).
Springer DOI
1504
computational complexity
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Zou, C.[Cheng],
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Scene flow for 3D laser scanner and camera system,
IET-IPR(12), No. 4, April 2018, pp. 612-618.
DOI Link
1804
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Learning motion field of LiDAR point cloud with convolutional
networks,
PRL(125), 2019, pp. 514-520.
Elsevier DOI
1909
Motion field, CNNs, LiDAR
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Zou, C.[Cheng],
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Zhang, J.W.[Jian-Wei],
Static map reconstruction and dynamic object tracking for a camera and
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IET-CV(12), No. 4, June 2018, pp. 384-392.
DOI Link
1805
BibRef
Lv, Z.Y.[Zhao-Yang],
Kim, K.[Kihwan],
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1810
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Semi-dense and robust image registration by shift adapted weighted
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Elsevier DOI
1909
Image correspondences, Stereo, Optical flow, Block-matching, Interpolation
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Navarro, J.,
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Variational scene flow and occlusion detection from a light field
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WSSIP16(1-4)
IEEE DOI
1608
cameras
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Elsevier DOI
1911
3D scene flow, Sensor fusion, Depth map upsampling
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Richardt, C.,
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Dense Wide-Baseline Scene Flow from Two Handheld Video Cameras,
3DV16(276-285)
IEEE DOI
1701
image reconstruction
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Lv, Z.Y.[Zhao-Yang],
Beall, C.[Chris],
Alcantarilla, P.F.[Pablo F.],
Li, F.[Fuxin],
Kira, Z.[Zsolt],
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A Continuous Optimization Approach for Efficient and Accurate Scene
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ECCV16(VIII: 757-773).
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Li, F.[Francis],
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Zelek, J.S.[John S.],
Hierarchical Grouping Approach for Fast Approximate RGB-D Scene Flow,
CRV16(140-147)
IEEE DOI
1612
RGB-D;scene flow;spectral clustering
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Srinivasan, P.P.[Pratul P.],
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Ng, R.[Ren],
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Oriented Light-Field Windows for Scene Flow,
ICCV15(3496-3504)
IEEE DOI
1602
Generalized optical flow.
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Sun, D.Q.[De-Qing],
Sudderth, E.B.[Erik B.],
Pfister, H.[Hanspeter],
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CVPR15(548-556)
IEEE DOI
1510
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Alhaija, H.A.[Hassan Abu],
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GCPR15(285-296).
Springer DOI
1511
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Zanfir, A.,
Sminchisescu, C.,
Large Displacement 3D Scene Flow with Occlusion Reasoning,
ICCV15(4417-4425)
IEEE DOI
1602
Adaptive optics
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Ferstl, D.[David],
Reinbacher, C.[Christian],
Riegler, G.[Gernot],
Ruther, M.[Matthias],
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aTGV-SF: Dense Variational Scene Flow through Projective Warping and
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3DV14(285-292)
IEEE DOI
1503
Cameras
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Roh, J.[Junha],
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A Fast TGV-l1 RGB-D Flow Estimation,
ISVC14(I: 151-161).
Springer DOI
1501
BibRef
Hornacek, M.[Michael],
Fitzgibbon, A.[Andrew],
Rother, C.[Carsten],
SphereFlow: 6 DoF Scene Flow from RGB-D Pairs,
CVPR14(3526-3533)
IEEE DOI
1409
BibRef
Ferstl, D.[David],
Riegler, G.[Gernot],
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CP-Census: A Novel Model for Dense Variational Scene Flow from RGB-D
Data,
BMVC14(xx-yy).
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1410
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Maier, R.[Robert],
Sturm, J.[Jürgen],
Cremers, D.[Daniel],
Submap-Based Bundle Adjustment for 3D Reconstruction from RGB-D Data,
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1411
See also Graph Based Bundle Adjustment for INS-Camera Calibration, A.
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Steinbrucker, F.[Frank],
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Cremers, D.[Daniel],
Real-time visual odometry from dense RGB-D images,
Dense11(719-722).
IEEE DOI
1201
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Zhang, X.W.[Xiao-Wei],
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Dense Scene Flow Based on Depth and Multi-channel Bilateral Filter,
ACCV12(III:140-151).
Springer DOI
1304
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Letouzey, A.[Antoine],
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Scene Flow from Depth and Color Images,
BMVC11(xx-yy).
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1110
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Cech, J.[Jan],
Sanchez-Riera, J.[Jordi],
Horaud, R.[Radu],
Scene flow estimation by growing correspondence seeds,
CVPR11(3129-3136).
IEEE DOI
1106
Flow in stereo
See also Topologically-robust 3D shape matching based on diffusion geometry and seed growing.
BibRef
Chapter on Optical Flow Field Computations and Use continues in
Error Analysis, Evaluation for Optical Flow .