Unfolding an Indoor Origami World - Peopledfouhey/2014/origami/origami_v4.pdf · Constraints for...
Transcript of Unfolding an Indoor Origami World - Peopledfouhey/2014/origami/origami_v4.pdf · Constraints for...
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Unfolding an Indoor Origami World
David Fouhey, Abhinav Gupta, Martial Hebert
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Local Evidence
4 Hoiem et al. 2005, Saxena et al. 2005, Fouhey et al. 2013, etc.
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Constraints
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Constraints for Single Image 3D
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Local Smoothness
Low Level, Generic
Hoiem et al. 2005, Saxena et al. 2005, 2008, Munoz et al., 2009, etc.
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Constraints for Single Image 3D
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Local Smoothness
Low Level, Generic
Hoiem et al. 2005, Saxena et al. 2005, 2008, Munoz et al., 2009, etc.
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Constraints for Single Image 3D
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Low Level, Generic
High Level, Physical
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High Level, Physical
Constraints for Single Image 3D
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Local Smoothness
Low Level, Generic
Coughlan and Yuille 2000, etc.
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High Level, Physical
Constraints for Single Image 3D
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Local Smoothness
Low Level, Generic
Hedau et al. 2009, Del Pero et al., 2011, Wang et al., 2012, Schwing et al. 2012, etc.
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High Level, Physical
Constraints for Single Image 3D
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Local Smoothness
Low Level, Generic
Lee et al. 2010, Xiao et al. 2012, Zhao et al. 2013, Schwing et al., 2013, etc.
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High Level, Physical
Constraints for Single Image 3D
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Low Level, Generic
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Mid-level in the Past
13 Huffman 71, Clowes 71, Kanade 80, 81 Sugihara 86, Malik 87, etc.
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Our Mid-Level Constraints
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This Work
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Input: Single Image
Output: Discrete Scene Parse
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Overview
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Parameterization Formulation
Experimental Results
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Overview
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Parameterization Formulation
Experimental Results
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Parameterization
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Parameterization
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vp1
vp2
vp3
VP Estimator from Hedau et al., 2009
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Parameterization
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Two VPs give grid cell
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Encoding Surface Normals
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Encoding Surface Normals
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Encoding Surface Normals
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Encoding Surface Normals
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x1,…, x400 x401,…, x800 x801,…, x1200
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Related Parameterizations
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vp1
vp3
x2
x1
x3
x4
Hedau et al., 2009; Wang et al. 2010, Schwing et al., 2012, 2013
vp2
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Overview
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Parameterization Formulation
Experimental Results
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Parameterization
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Formulation
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Unaries
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Unaries
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Low c Any 3D Evidence
High c
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Unaries
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…
Input 3D Primitive Bank
Local: Data-Driven 3D Primitives
Fouhey, Gupta, Hebert, 2013
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Unaries
32 Hedau, Hoiem, Forsyth, 2009
Global: Cuboid Fit + Clutter Mask
Input Predicted Walls Clutter Mask
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Binaries
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Convex/Concave Constraints
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Convex (+) Concave (-)
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Convex/Concave Constraints
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Detected Concave (-)
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Convex/Concave Constraints
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Detected Concave (-)
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Convex/Concave Constraints
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Detected Concave (-)
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Convex/Concave Constraints
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Detected Concave (-)
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Convex/Concave Constraints
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Detected Concave (-)
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Detecting Convex/Concave
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Ground-Truth Discontinuities similar to Gupta, Arbelaez, Malik, 2013 3DP from Fouhey, Gupta, Hebert, 2013
Input 3D Primitive Bank
…
Use 3DP to Transfer Discontinuities
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Smoothness
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Constraints
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Solving the Model
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Overview
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Parameterization Formulation
Experimental Results
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Dataset
NYU Depth v2: 795 Train, 654 Test
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Qualitative Results
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Qualitative Results
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Qualitative Results
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Qualitative Results
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Surface Connection Graphs
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Convex Concave
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Baseline
Primary Baseline: 3D Primitives
51 Fouhey, Gupta, Hebert, 2013
Output Input
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Quantitative Results
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Summary Stats (⁰) (Lower Better)
% Good Pixels (Higher Better)
11.25⁰ 22.5⁰ 30⁰ Mean Median
3DP 35.9 52.0 57.8 36.0 20.5 49.4
Hedau et al. 34.2 49.3 54.4 40.0 23.5 54.1
RMSE
Lee et al. 18.6 38.6 49.9 43.3 36.3 54.6
Proposed 37.6 53.3 58.9 35.1 19.2 48.7
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Quantitative Results
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Failure Modes
Mistaken but Confident Evidence
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Failure Modes
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Missing High-Level Modeling
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Conclusions
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Single Image
Parameterization
Formulation
Discrete Parse
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Thank You
57