9.11.3.1 Intrinsic Image Analysis, Intrinsic Image Decomposition

Chapter Contents (Back)
Intrinsic Images. Some similar papers: See also Gaussian Sphere (EGI), Intrinsic Images, and Surface Orientations. Especially See: See also Interpreting Line Drawings as Three-Dimensional Surfaces.

Matsushita, Y., Nishino, K.[Ko], Ikeuchi, K., Sakauchi, M.,
Illumination Normalization with Time-Dependent Intrinsic Images for Video Surveillance,
PAMI(26), No. 10, October 2004, pp. 1336-1347.
IEEE Abstract. 0409
BibRef
Earlier: CVPR03(I: 3-10).
IEEE DOI 0307
BibRef

Matsushita, Y., Nishino, K.[Ko], Ikeuchi, K., Sakauchi, M.,
Shadow elimination for robust video surveillance,
Motion02(15-21).
IEEE DOI 0303
BibRef

Matsushita, Y.[Yasuyuki], Lin, S.[Stephen], Shum, H.Y.[Heung-Yeung], Tong, X.[Xin], Kang, S.B.[Sing Bing],
Lighting and Shadow Interpolation Using Intrinsic Lumigraphs,
IJIG(4), No. 4, October 2004, pp. 585-604. 0410
BibRef

Shen, L.[Li], Tan, P.[Ping], Lin, S.[Stephen],
Intrinsic image decomposition with non-local texture cues,
CVPR08(1-7).
IEEE DOI 0806
BibRef

Fusiello, A.[Andrea], Farenzena, M.[Michela], Busti, A., Benedetti, A.,
Computing rigorous bounds to the accuracy of calibrated stereo reconstruction,
VISP(152), No. 6, December 2005, pp. 695-701. 0512
BibRef
Earlier: A2, A3, A1, A4:
Rigorous accuracy bounds for calibrated stereo reconstruction,
ICPR04(IV: 288-292).
IEEE DOI 0409
BibRef

Farenzena, M.[Michela], Dovier, A.[Agostino],
Reconstruction with Interval Constraints Propagation,
CVPR06(I: 1185-1190).
IEEE DOI 0606
BibRef

Farenzena, M.[Michela], Fusiello, A.[Andrea],
Stabilizing 3D modeling with geometric constraints propagation,
CVIU(113), No. 11, November 2009, pp. 1147-1157.
Elsevier DOI 0910
BibRef
Earlier:
3D surface models by geometric constraints propagation,
CVPR08(1-8).
IEEE DOI 0806
BibRef
Earlier:
Recovering Intrinsic Images using an Illumination Invariant Image,
ICIP07(III: 485-488).
IEEE DOI 0709
3D modeling; Geometric constraints BibRef

Tappen, M.F.[Marshall F.], Freeman, W.T.[William T.], Adelson, E.H.[Edward H.],
Recovering Intrinsic Images from a Single Image,
PAMI(27), No. 9, September 2005, pp. 1459-1472.
IEEE DOI 0508
BibRef
Earlier: MIT AIMAIM-2002-015, September 2002.
WWW Link. 0306
Given color and lighting direction, recover shading and reflection. BibRef

Tappen, M.F.[Marshall F.], Adelson, E.H.[Edward H.], Freeman, W.T.[William T.],
Estimating Intrinsic Component Images using Non-Linear Regression,
CVPR06(II: 1992-1999).
IEEE DOI 0606
BibRef

Tappen, M.F.[Marshall F.],
Recovering shape from a single image of a mirrored surface from curvature constraints,
CVPR11(2545-2552).
IEEE DOI 1106
BibRef

Khan, N.[Nazar], Tran, L.[Lam], Tappen, M.F.[Marshall F.],
Training many-parameter shape-from-shading models using a surface database,
3DIM09(1433-1440).
IEEE DOI 0910
BibRef

Johnson, M.K.[Micah K.], Adelson, E.H.[Edward H.],
Shape estimation in natural illumination,
CVPR11(2553-2560).
IEEE DOI 1106
BibRef

Johnson, M.K.[Micah K.], Adelson, E.H.[Edward H.],
Retrographic sensing for the measurement of surface texture and shape,
CVPR09(1070-1077).
IEEE DOI 0906
Device for 2.5D scanner. Haptic, photometric stereo. flecks of paint in clear flexible surface, image from the other side. Very detailed 3D no matter the surface. BibRef

Zoran, D., Isola, P.[Phillip], Krishnan, D., Freeman, W.T.[William T.],
Learning Ordinal Relationships for Mid-Level Vision,
ICCV15(388-396)
IEEE DOI 1602
Context. Pairwise relationships. Not metric properties. BibRef

Cole, F.[Forrester], Isola, P.[Phillip], Freeman, W.T.[William T.], Durand, F.[Frédo], Adelson, E.H.[Edward H.],
Shapecollage: Occlusion-Aware, Example-Based Shape Interpretation,
ECCV12(III: 665-678).
Springer DOI 1210
and line drawings BibRef

Johnson, M.K.[Micah K.], Cole, F.[Forrester], Raj, A.[Alvin], Adelson, E.H.[Edward H.],
Microgeometry Capture using an Elastomeric Sensor,
SIGGraph11(xx-yy).
PDF File. 1109
System, GelSight. More details based on earlier retrographic sensing. The GelSight System. BibRef

Shen, L.[Li], Yeo, C.H.[Chuo-Hao], Hua, B.S.[Binh-Son],
Intrinsic Image Decomposition Using a Sparse Representation of Reflectance,
PAMI(35), No. 12, 2013, pp. 2904-2915.
IEEE DOI 1311
BibRef
Earlier: A1, A2, Only:
Intrinsic images decomposition using a local and global sparse representation of reflectance,
CVPR11(697-704).
IEEE DOI 1106
Image color analysis BibRef

Shen, J., Yang, X., Li, X., Jia, Y.,
Intrinsic Image Decomposition Using Optimization and User Scribbles,
Cyber(43), No. 2, April 2013, pp. 425-436.
IEEE DOI 1303
BibRef

Barron, J.T.[Jonathan T.], Malik, J.[Jitendra],
Shape, Illumination, and Reflectance from Shading,
PAMI(37), No. 8, August 2015, pp. 1670-1687.
IEEE DOI 1507
BibRef
Earlier:
Shape, albedo, and illumination from a single image of an unknown object,
CVPR12(334-341).
IEEE DOI 1208
BibRef
Earlier:
High-frequency shape and albedo from shading using natural image statistics,
CVPR11(2521-2528).
IEEE DOI 1106
Computer vision BibRef

Barron, J.T.[Jonathan T.], Malik, J.[Jitendra],
Intrinsic Scene Properties from a Single RGB-D Image,
PAMI(38), No. 4, April 2016, pp. 690-703.
IEEE DOI 1603
BibRef
Earlier: CVPR13(17-24)
IEEE DOI 1309
BibRef
And:
Color Constancy, Intrinsic Images, and Shape Estimation,
ECCV12(IV: 57-70).
Springer DOI 1210
Computational modeling BibRef

Barron, J.T.,
Convolutional Color Constancy,
ICCV15(379-387)
IEEE DOI 1602
Cognition BibRef

Hauagge, D.C.[Daniel C.], Wehrwein, S.[Scott], Bala, K.[Kavita], Snavely, N.[Noah],
Photometric Ambient Occlusion for Intrinsic Image Decomposition,
PAMI(38), No. 4, April 2016, pp. 639-651.
IEEE DOI 1603
BibRef
Earlier:
Photometric Ambient Occlusion,
CVPR13(2515-2522)
IEEE DOI 1309
Cameras. albedo; image stacks; intrinsic images. Stack of images from one viewpoint. ambient occlusion: how much light can reach a point in the scene. BibRef

Kovacs, B.[Balazs], Bell, S.[Sean], Snavely, N.[Noah], Bala, K.[Kavita],
Shading Annotations in the Wild,
CVPR17(850-859)
IEEE DOI 1711
Image color analysis, Image decomposition, Lighting, Shape, Surface acoustic waves, Surface, treatment BibRef

Xing, G.Y.[Guan-Yu], Liu, Y.L.[Yan-Li], Zhang, W.[Wanfa], Ling, H.B.[Hai-Bin],
Light mixture intrinsic image decomposition based on a single RGB-D image,
VC(32), No. 6-8, June 2016, pp. 1013-1023.
Springer DOI 1608
BibRef

Jin, X., Gu, Y.,
Superpixel-Based Intrinsic Image Decomposition of Hyperspectral Images,
GeoRS(55), No. 8, August 2017, pp. 4285-4295.
IEEE DOI 1708
Feature extraction, Hyperspectral imaging, Image segmentation, Lighting, Mathematical model, Matrix decomposition, Hyperspectral image, intrinsic image decomposition (IID), optimization, superpixel BibRef

Han, G., Xie, X., Lai, J., Zheng, W.S.,
Learning an Intrinsic Image Decomposer Using Synthesized RGB-D Dataset,
SPLetters(25), No. 6, June 2018, pp. 753-757.
IEEE DOI 1806
feature extraction, image colour analysis, image texture, learning (artificial intelligence), neural nets, intrinsic image BibRef

Jin, X., Gu, Y., Liu, T.,
Intrinsic Image Recovery From Remote Sensing Hyperspectral Images,
GeoRS(57), No. 1, January 2019, pp. 224-238.
IEEE DOI 1901
Hyperspectral imaging, Pigments, Feature extraction, Lighting, Mathematical model, Classification, feature extraction, reflectance BibRef


Cheng, L., Zhang, C., Liao, Z.,
Intrinsic Image Transformation via Scale Space Decomposition,
CVPR18(656-665)
IEEE DOI 1812
Laplace equations, Task analysis, Training, Space exploration, Network architecture, Computer architecture, Transforms BibRef

Huang, Q., Zhu, W., Zhao, Y., Chen, L., Wang, Y., Yue, T., Cao, X.,
Multispectral Image Intrinsic Decomposition via Subspace Constraint,
CVPR18(6430-6439)
IEEE DOI 1812
Lighting, Image color analysis, Image segmentation, Geometry, Image decomposition, Subspace constraints, Color BibRef

Baslamisli, A.S., Le, H., Gevers, T.,
CNN Based Learning Using Reflection and Retinex Models for Intrinsic Image Decomposition,
CVPR18(6674-6683)
IEEE DOI 1812
Lighting, Light sources, Standards, Computational modeling, Convolutional neural networks, Mathematical model BibRef

Fan, Q., Yang, J., Hua, G., Chen, B., Wipf, D.,
Revisiting Deep Intrinsic Image Decompositions,
CVPR18(8944-8952)
IEEE DOI 1812
Training, Image edge detection, Image decomposition, Benchmark testing, Optimization, Training data, Lighting BibRef

Li, Z., Snavely, N.,
Learning Intrinsic Image Decomposition from Watching the World,
CVPR18(9039-9048)
IEEE DOI 1812
Training, Lighting, Videos, Image sequences, Image reconstruction, Sparse matrices BibRef

Han, G., Xie, X., Zheng, W., Lai, J.,
Learning Intrinsic Image Decomposition by Deep Neural Network with Perceptual Loss,
ICPR18(91-96)
IEEE DOI 1812
computer vision, feature extraction, learning (artificial intelligence), neural nets, Image decomposition BibRef

Li, Z.Q.[Zheng-Qi], Snavely, N.[Noah],
CGIntrinsics: Better Intrinsic Image Decomposition Through Physically-Based Rendering,
ECCV18(III: 381-399).
Springer DOI 1810
BibRef

Garces, E., Reinhard, E.,
Light-Field Surface Color Segmentation with an Application to Intrinsic Decomposition,
WACV18(1480-1488)
IEEE DOI 1806
image colour analysis, image segmentation, dense light fields, fully automatic segmentation pipeline, intrinsic decomposition, Surface treatment BibRef

Baslamisli, A.S.[Anil S.], Groenestege, T.T.[Thomas T.], Das, P.[Partha], Le, H.A.[Hoang-An], Karaoglu, S.[Sezer], Gevers, T.[Theo],
Joint Learning of Intrinsic Images and Semantic Segmentation,
ECCV18(VI: 289-305).
Springer DOI 1810
BibRef

Muhammad, S.[Siraj], Dailey, M.N.[Matthew N.], Sato, I.[Imari], Majeed, M.F.[Muhammad F.],
Handling Specularity in Intrinsic Image Decomposition,
ICIAR18(107-115).
Springer DOI 1807
BibRef

Nestmeyer, T., Gehler, P.V.,
Reflectance Adaptive Filtering Improves Intrinsic Image Estimation,
CVPR17(1771-1780)
IEEE DOI 1711
Benchmark testing, Estimation, Image color analysis, Image decomposition, Standards BibRef

Kim, S.R.[Seung-Ryong], Park, K.[Kihong], Sohn, K.H.[Kwang-Hoon], Lin, S.[Stephen],
Unified Depth Prediction and Intrinsic Image Decomposition from a Single Image via Joint Convolutional Neural Fields,
ECCV16(VIII: 143-159).
Springer DOI 1611
BibRef

Shi, J., Dong, Y., Su, H., Yu, S.X.,
Learning Non-Lambertian Object Intrinsics Across ShapeNet Categories,
CVPR17(5844-5853)
IEEE DOI 1711
Decoding, Lighting, Machine learning, Mathematical model, Rendering (computer graphics), Spatial resolution, Training BibRef

Xie, D.H.[De-Hua], Liu, S.C.[Shuai-Cheng], Lin, K.[Kaimo], Zhu, S.Y.[Shu-Yuan], Zeng, B.[Bing],
Intrinsic decomposition for stereoscopic images,
ICIP16(1744-1748)
IEEE DOI 1610
Avalanche photodiodes. Reflectance and shading. BibRef

Laffont, P.Y., Bazin, J.C.,
Intrinsic Decomposition of Image Sequences from Local Temporal Variations,
ICCV15(433-441)
IEEE DOI 1602
Reflectance and shading. Geometry BibRef

Zhou, T., Krähenbühl, P.[Philipp], Efros, A.A.,
Learning Data-Driven Reflectance Priors for Intrinsic Image Decomposition,
ICCV15(3469-3477)
IEEE DOI 1602
Computer vision BibRef

Narihira, T., Maire, M., Yu, S.X.,
Direct Intrinsics: Learning Albedo-Shading Decomposition by Convolutional Regression,
ICCV15(2992-2992)
IEEE DOI 1602
Color BibRef

Jeon, J.[Junho], Cho, S.H.[Sung-Hyun], Tong, X.[Xin], Lee, S.Y.[Seung-Yong],
Intrinsic Image Decomposition Using Structure-Texture Separation and Surface Normals,
ECCV14(VII: 218-233).
Springer DOI 1408
using RGB-D image. also use texture. BibRef

Shelhamer, E.[Evan], Barron, J.T., Darrell, T.J.[Trevor J.],
Scene Intrinsics and Depth from a Single Image,
IR15(235-242)
IEEE DOI 1602
Cognition; Lighting; Optimization; Pipelines; Sensors; Shape; Training BibRef

Kong, N.[Naejin], Black, M.J.[Michael J.],
Intrinsic Depth: Improving Depth Transfer with Intrinsic Images,
ICCV15(3514-3522)
IEEE DOI 1602
Cameras BibRef

Kong, N.[Naejin], Gehler, P.V.[Peter V.], Black, M.J.[Michael J.],
Intrinsic Video,
ECCV14(II: 360-375).
Springer DOI 1408
extracting temporally coherent albedo and shading from video alone. BibRef

Chen, Q.[Qifeng], Koltun, V.[Vladlen],
Photographic Image Synthesis with Cascaded Refinement Networks,
ICCV17(1520-1529)
IEEE DOI 1802
BibRef
Earlier:
Fast MRF Optimization with Application to Depth Reconstruction,
CVPR14(3914-3921)
IEEE DOI 1409
BibRef
Earlier:
A Simple Model for Intrinsic Image Decomposition with Depth Cues,
ICCV13(241-248)
IEEE DOI 1403
feedforward neural nets, image resolution, regression analysis, 2-megapixel resolution, cascaded refinement networks. Depth Reconstruction; MRF Optimization. RGB-D images. estimate albedo and shading fields. BibRef

Yu, J.Z.[Jin-Ze],
Rank-constrained PCA for intrinsic images decomposition,
ICIP16(3578-3582)
IEEE DOI 1610
Computer vision BibRef

Yu, J.Z.[Jin-Ze], Sato, Y.[Yoichi],
Fast sparse edge-based intrinsic image decomposition guided by chromaticity gradients,
ICIP15(3753-3757)
IEEE DOI 1512
L0-norm BibRef

Liu, Y.L.[Yuan-Liu], Yuan, Z.J.[Ze-Jian], Zheng, N.N.[Nan-Ning],
Intrinsic Image Decomposition from Pair-Wise Shading Ordering,
ACCV14(V: 83-98).
Springer DOI 1504
intrinsic images. BibRef

Liao, Z.C.[Zi-Cheng], Rock, J.[Jason], Wang, Y.[Yang], Forsyth, D.A.[David A.],
Non-parametric Filtering for Geometric Detail Extraction and Material Representation,
CVPR13(963-970)
IEEE DOI 1309
Geometric detail; intrinsic image decomposition; material representation. Separate description of detail from intrinsic image. Coarse shading plus details. Enables editing. BibRef

Kumar, P.,
Intrinsic Image Based Moving Object Cast Shadow Removal in Image Sequences,
DICTA11(410-415).
IEEE DOI 1205
BibRef

Shen, J.B.[Jian-Bing], Yang, X.S.[Xiao-Shan], Jia, Y.D.[Yun-De], Li, X.L.[Xue-Long],
Intrinsic images using optimization,
CVPR11(3481-3487).
IEEE DOI 1106
Similar neighboring colors are similar reflectance properties. BibRef

Grosse, R.[Roger], Johnson, M.K.[Micah K.], Adelson, E.H.[Edward H.], Freeman, W.T.[William T.],
Ground truth dataset and baseline evaluations for intrinsic image algorithms,
ICCV09(2335-2342).
IEEE DOI 0909
Dataset, Shading. For shading and reflectance computations. BibRef

Jiang, X.Y.[Xiao-Yue], Schofield, A.J.[Andrew J.], Wyatt, J.L.[Jeremy L.],
Correlation-Based Intrinsic Image Extraction from a Single Image,
ECCV10(IV: 58-71).
Springer DOI 1009
Luminance. BibRef

El-Melegy, M.T.,
Image Intrinsic Values from Shading Information,
ICIP05(II: 1166-1169).
IEEE DOI 0512
BibRef

Weiss, Y.[Yair],
Deriving Intrinsic Images from Image Sequences,
ICCV01(II: 68-75).
IEEE DOI 0106
Stationary camera, changing sun. Multiple images give the reflectance image separate from the illumination. BibRef

Chapter on 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings continues in
Dual/Gradient Space Concepts .


Last update:Aug 10, 2019 at 15:07:15