I completed my PhD under the supervision of Prof. Peter V. Gehler at MPI and joined as a research scientist at Nvidia Research. My work lies at the intersection of Machine Learning and Computer Vision. Specifically, I am working on leveraging machine learning techniques for better inference in computer vision applications. The main research question is how to make use of learning techniques such as deep neural networks and random forests for inference in structured prediction frameworks.
See my homepage for recent updates: https://varunjampani.github.io/
(Jan’13 – Dec'16)
Max-Planck Institute for Intelligent Systems and University of Tübingen, Tübingen, Germany
Doctor of Philosophy (PhD) in computer vision and machine learning (Grade: summa cum laude)
Thesis Title: Learning Inference Models for Computer Vision
(July’09 - Dec ’12)
International Institute of Information Technology, Hyderabad (IIIT-H), India
Master of Science (MS) by Research in computer sciences
Thesis Title: A Study of X-ray Image Perception for Pneumoconiosis Diagnosis
(July ’05 – May ’09)
International Institute of Information Technology, Hyderabad (IIIT-H), India
Bachelor of Technology (BTech) with Honours in computer sciences (CGPA: 9.68/10.0)
Gold Medalist and member of Dean’s list for all the semesters
The following are some public codes that I have contributed to during my PhD:
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Sevilla-Lara, L., Liao, Y., Guney, F., Jampani, V., Geiger, A., Black, M. J.
On the Integration of Optical Flow and Action Recognition
In German Conference on Pattern Recognition (GCPR), October 2018 (inproceedings)
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Gadde, R., Jampani, V., Gehler, P. V.
Semantic Video CNNs through Representation Warping
In Proceedings IEEE International Conference on Computer Vision (ICCV), IEEE, Piscataway, NJ, USA, IEEE International Conference on Computer Vision (ICCV), October 2017 (inproceedings) Accepted
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Jampani, V., Gadde, R., Gehler, P. V.
Video Propagation Networks
In Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017, IEEE, Piscataway, NJ, USA, IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017 (inproceedings)
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Jampani, V.
Learning Inference Models for Computer Vision
MPI for Intelligent Systems and University of Tübingen, 2017 (phdthesis)
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Gadde, R., Jampani, V., Marlet, R., Gehler, P.
Efficient 2D and 3D Facade Segmentation using Auto-Context
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017 (article)
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Gadde, R., Jampani, V., Kiefel, M., Kappler, D., Gehler, P.
Superpixel Convolutional Networks using Bilateral Inceptions
In European Conference on Computer Vision (ECCV), Lecture Notes in Computer Science, Springer, 14th European Conference on Computer Vision, October 2016 (inproceedings)
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Sevilla-Lara, L., Sun, D., Jampani, V., Black, M. J.
Optical Flow with Semantic Segmentation and Localized Layers
In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 3889-3898, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)
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Jampani, V., Kiefel, M., Gehler, P. V.
Learning Sparse High Dimensional Filters: Image Filtering, Dense CRFs and Bilateral Neural Networks
In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), pages: 4452-4461, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2016 (inproceedings)
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Jampani, V., Nowozin, S., Loper, M., Gehler, P. V.
The Informed Sampler: A Discriminative Approach to Bayesian Inference in Generative Computer Vision Models
In Special Issue on Generative Models in Computer Vision and Medical Imaging, 136, pages: 32-44, Elsevier, July 2015 (inproceedings)
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Kiefel, M., Jampani, V., Gehler, P. V.
Permutohedral Lattice CNNs
In ICLR Workshop Track, ICLR, May 2015 (inproceedings)
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Jampani, V., Eslami, S. M. A., Tarlow, D., Kohli, P., Winn, J.
Consensus Message Passing for Layered Graphical Models
In Eighteenth International Conference on Artificial Intelligence and Statistics (AISTATS), 38, pages: 425-433, JMLR Workshop and Conference Proceedings, Eighteenth International Conference on Artificial Intelligence and Statistics, May 2015 (inproceedings)
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Jampani, V., Gadde, R., Gehler, P. V.
Efficient Facade Segmentation using Auto-Context
In Applications of Computer Vision (WACV), 2015 IEEE Winter Conference on, pages: 1038-1045, IEEE, WACV,, January 2015 (inproceedings)
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Jampani, V.
A Study of X-Ray Image Perception for Pneumoconiosis Detection
IIIT-Hyderabad, Hyderabad, India, January 2013 (mastersthesis)
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Jampani, V., Ujjwal, , Sivaswamy, J., Vaidya, V.
Assessment of Computational Visual Attention Models on Medical Images
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing, pages: 80:1-80:8, ACM, Mumbai, India, December 2012 (conference)
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Jampani, V., Vaidya, V., Sivaswamy, J., Tourani, K. L.
Role of expertise and contralateral symmetry in the diagnosis of pneumoconiosis: an experimental study
In Proc. SPIE 7966, Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, 2011, Florida, March 2011 (inproceedings)
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Jampani, V., Ramos, G., Drucker, S.
ImageFlow: Streaming Image Search
MSR-TR-2010-148, Microsoft Research, Redmond, 2010 (techreport)