Dr. Kripasindhu Sarkar
E-Mail: | kripasindhu.sarkar@dfki.de |
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Position: | Researcher |
Working on the problem of 3D modeling and Object Detection with CNNs.
Simple domain adaptation for CAD based object recognition
International Conference on Pattern Recognition Applications and Methods. International Conference on Pattern Recognition Applications and Methods (ICPRAM-2019) February 19-21 Prague Czech Republic Scitepress 2019 .
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Learning 3D Shapes as Multi-Layered Height-maps using 2D Convolutional Networks
. European Conference on Computer Vision (ECCV-2018), September 8-14, Munich, Germany, Springer International Publishing, 2018.
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3D Shape Processing by Convolutional Denoising Autoencoders on Local Patches
IEEE Winter Conference on Applications of Computer Vision (WACV-18), March 12-15, Lake Tahoe, NV, USA
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Denoising of point-clouds based on structured dictionary learning
Eurographics Symposium on Geometry Processing (SGP-2018), July 7-11, Paris, France
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Learning 3D Shapes as Multi-Layered Height-maps using 2D Convolutional Networks
Computer Vision -- ECCV 2018 European Conference on Computer Vision (ECCV-2018), September 8-14, Munich, Germany
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Structured Low-Rank Matrix Factorization for Point-Cloud Denoising
International Conference on 3D Vision (3DVision-2018), September 5-8, Verona, Italy
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Trained 3D Models for CNN based Object Recognition
Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, (VISIGRAPP 2017) International Conference on Computer Vision Theory and Applications (VISAPP-17)
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Learning quadrangulated patches for 3D shape parameterization and completion
International Conference on 3D Vision 2017 International Conference on 3DVision (3DV-2017), 5th, October 10-12, Qingdao, China
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Feature-augmented Trained Models for 6DOF Object Recognition and Camera Calibration
Proceedings of the International Conference on Computer Vision Theory and Applications International Conference on Computer Vision Theory and Applications (VISAPP-16)
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