iccv iccv2013 iccv2013-308 iccv2013-308-reference knowledge-graph by maker-knowledge-mining
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Author: Joseph J. Lim, Hamed Pirsiavash, Antonio Torralba
Abstract: We address the problem of localizing and estimating the fine-pose of objects in the image with exact 3D models. Our main focus is to unify contributions from the 1970s with recent advances in object detection: use local keypoint detectors to find candidate poses and score global alignment of each candidate pose to the image. Moreover, we also provide a new dataset containing fine-aligned objects with their exactly matched 3D models, and a set of models for widely used objects. We also evaluate our algorithm both on object detection and fine pose estimation, and show that our method outperforms state-of-the art algorithms.
[1] N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005. 2
[2] M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and
[3]
[4]
[5]
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16] A. Zisserman. The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results. 6 P. Felzenszwalb and D. Huttenlocher. Efficient graph-based image segmentation. IJCV, 59(2): 167–181, 2004. 3 P. F. Felzenszwalb, R. B. Girshick, and D. McAllester. Discriminatively trained deformable part models, release 4. 6, 8 S. Fidler, S. J. Dickinson, and R. Urtasun. 3d object detection and viewpoint estimation with a deformable 3d cuboid model. In NIPS, 2012. 2 M. Fisher and P. Hanrahan. Context-based search for 3d models. ACM Trans. Graph., 29(6), Dec. 2010. 2 S. Gupta, P. Arbelaez, and J. Malik. Perceptual organization and recognition of indoor scenes from RGB-D images. In CVPR, 2013. 2 B. Hariharan, J. Malik, and D. Ramanan. Discriminative decorrelation for clustering and classification. In ECCV, 2012. 3, 6, 8 M. Hejrati and D. Ramanan. Analyzing 3d objects in cluttered images. In NIPS, 2012. 2 P. Henry, M. Krainin, E. Herbst, X. Ren, and D. Fox. Rgbd mapping: Using depth cameras for dense 3d modeling of indoor environments. In RGB-D: Advanced Reasoning with Depth Cameras Workshop in conjunction with RSS, 2010. 2 J. J. Lim, C. L. Zitnick, and P. Dollar. Sketch tokens: A learned mid-level representation for contour and object detection. In CVPR, 2013. 4 D. Lowe. Fitting parameterized three-dimensional models to images. PAMI, 1991. 1, 3 D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004. 2 J. L. Mundy. Object recognition in the geometric era: A retrospective. In Toward CategoryLevel Object Recognition, volume 4170 of Lecture Notes in Computer Science, pages 3–29. Springer, 2006. 1 T. Ojala, M. Pietikinen, and T. Menp. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. PAMI, 2002. 4 B. Pepik, P. Gehler, M. Stark, and B. Schiele. 3d2pm - 3d deformable
[17]
[18]
[19]
[20]
[21] part models. In ECCV, 2012. 2 F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce. 3d object modeling and recognition using local affine-invariant image descriptors and multi-view spatial constraints. IJCV, 66:2006, 2006. 1 S. Satkin, J. Lin, and M. Hebert. Data-driven scene understanding from 3D models. In BMVC, 2012. 4 Y. Xiang and S. Savarese. Estimating the aspect layout of object categories. In CVPR, 2012. 2 J. Xiao, B. Russell, and A. Torralba. Localizing 3d cuboids in singleview images. In NIPS. 2012. 2, 4 Y. Zhao and S.-C. Zhu. Image parsing via stochastic scene grammar. In NIPS, 2011. 2 222999999999