Beyond PASCAL: A Benchmark for 3D Object Detection in the...
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Beyond PASCAL: A Benchmark for 3D Object Detection in the Wild
Yu Xiang1,2, Roozbeh Mottaghi2 and Silvio Savarese2 1University of Michigan, 2Stanford University
In IEEE Winter Conference on Applications of Computer Vision (WACV), 2014.
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Goal
• Build a large scale dataset for 3D object detection and pose estimation
Y. Xiang, R. Mottaghi and S. Savarese, WACV'14 2
elevation
distance
azimuth
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3D Object Dataset
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[1] S. Savarese and L. Fei-Fei. 3d generic object categorization, localization and pose estimation. In ICCV, 2007.
#category #instance Non-centered objects
Dense viewpoint
3D Shape
3D Object [1] 10 100
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EPFL Car Dataset
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[2] M. Ozuysal, V. Lepetit, and P. Fua. Pose estimation for category specific multiview object localization. In CVPR, 2009.
#category #instance Non-centered objects
Dense viewpoint
3D Shape
3D Object [1] 10 100
EPFL Car [2] 1 20
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PASCAL VOC Dataset
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[3] M. Everingham, L. Van Gool, C. K. I.Williams, J.Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. IJCV, 2010.
#category #instance Non-centered objects
Dense viewpoint
3D Shape
3D Object [1] 10 100
EPFL Car [2] 1 20
PASCAL VOC [3] 20 27,450
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KITTI Dataset
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[4] A. Geiger, P. Lenz, and R. Urtasun. Are we ready for autonomous driving? the kitti vision benchmark suite. In CVPR, 2012.
#category #instance Non-centered objects
Dense viewpoint
3D Shape
3D Object [1] 10 100
EPFL Car [2] 1 20
PASCAL VOC [3] 20 27,450
KITTI [4] 3 80,256
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Our Contribution: PASCAL3D+
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#category #instance Non-centered objects
Dense viewpoint
3D Shape
3D Object [1] 10 100
EPFL Car [2] 1 20
PASCAL VOC [3] 20 27,450
KITTI [4] 3 80,256
PASCAL3D+ (Ours) 12 30,899
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Annotation Tool
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CAD alignment
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CAD alignment
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CAD Models
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CAD Models
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CAD Models
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Statistics
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Viewpoint Distribution
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Statistics
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Occlusion Percentage
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Object Detection and Viewpoint Estimation
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DPM with 24 Views
Detection 29.5
Viewpoint 12.1
• DPM: P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part based models. PAMI, 2010.
PASCAL3D+ website: http://cvgl.stanford.edu/projects/pascal3d.html Welcome to submit your results!
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Conclusion
• PASCAL3D+: a large scale 3D object detection dataset in the wild
• Benchmark both 2D and 3D object detection methods
• Benefit research in 3D object detection and pose estimation
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Our Future Work
• More categories ≈100
• More CAD models per category
• Improve alignment with CAD models
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