New Techniques for Automated Architectural Reconstruction from Photographs
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Modelling and Interpretation of Architecture from Several Images
International Journal of Computer Vision
"GrabCut": interactive foreground extraction using iterated graph cuts
ACM SIGGRAPH 2004 Papers
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Towards Multi-View Object Class Detection
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Web-based 3D Reconstruction Service
Machine Vision and Applications
Poisson surface reconstruction
SGP '06 Proceedings of the fourth Eurographics symposium on Geometry processing
3-D Depth Reconstruction from a Single Still Image
International Journal of Computer Vision
Robust Object Detection with Interleaved Categorization and Segmentation
International Journal of Computer Vision
Putting Objects in Perspective
International Journal of Computer Vision
PatchMatch: a randomized correspondence algorithm for structural image editing
ACM SIGGRAPH 2009 papers
Image-based street-side city modeling
ACM SIGGRAPH Asia 2009 papers
Shape-from-recognition: Recognition enables meta-data transfer
Computer Vision and Image Understanding
Region filling and object removal by exemplar-based image inpainting
IEEE Transactions on Image Processing
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Object removal and inpainting approaches typically require a user to manually create a mask around occluding objects. While creating masks for a small number of images is possible, it rapidly becomes untenable for longer image sequences. Instead, we accomplish this step automatically using an object detection framework to explicitly recognize and remove several classes of occlusions. We propose using this technique to improve 3D urban reconstruction from street level imagery, in which building facades are frequently occluded by vegetation or vehicles. By assuming facades in the background are planar, 3D scene estimation provides important context to the inpainting process by restricting input sample patches to regions that are coplanar to the occlusion, leading to more realistic final textures. Moreover, because non-static and reflective occlusion classes tend to be difficult to reconstruct, explicitly recognizing and removing them improves the resulting 3D scene.