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Dan Raviv

Geometric Machine Learning (GML)

Research

My research is focused on machine learning problems with geometric flavor. The symbiosis between data-driven and model-driven methods opens up new and exciting possibilities to overcome limitations in the new era of machine learning.  The data we consume have a unique structure which we can further exploit in learning paradigm used, for example, in computer vision, medical imaging and robotics.

Latest Publications

Jou

1.  Full and partial symmetries of non-rigid shapes 

     Dan Raviv, A. M. Bronstein, M. M. Bronstein and R. Kimmel.

     International Journal of Computer Vision (IJCV), 89 (1), 2009.

​

2. Affine-invariant geodesic geometry of deformable 3D shapes

     Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and N. Sochen.

     Computers & Graphics Journal, 35 (3), 2011.

     Also published in Proc. Shape Modeling International, 2011. 

​

3. Design of aerosol face masks for children using computerized 3D face analysis

     Amirav, A. Luder, A. Halamish, Dan Raviv, R. Kimmel and M. Newhouse

     Journal of Aerosol Medicine and Pulmonary drug Delivery, 27 (4), 2013.

 

4. Scale invariant geometry of non-rigid shape

     Y. Aflalo, R. Kimmel and Dan Raviv

     SIAM Journal on Imaging Sciences (SIIMS), 6 (3), 2013.

 

5.  Graph Isomorphisms and Automorphisms via Spectral Signatures

    Dan Raviv, R. Kimmel and Alfred. M. Bruckstein

    Transactions on Pattern analysis and Machine Intelligence (TPAMI), 35 (8), 2013.

 

6.  Geometric and photometric data fusion in non-rigid shape analysis

    Kovnastsky, Dan Raviv, M. M. Bronstein, A. M. Bronstein, R. Kimmel 

    Numerical Mathematics: Theory, Methods and Applications, 6 (1), 2013. 

 

7. Hierarchical matching of non-rigid shapes

    Dan Raviv, A.  Dubrovina , R. Kimmel

    Numerical Mathematics: Theory, Methods and Applications, 6 (1), 2013.

​

8. Active printed materials for complex self-evolving deformations

    Dan Raviv, W. Zhao, C. McKnelly, A. Papadopoulou, A. Kadambi, B. Shi, S. Hirsch, 

    D. Dikovski, M. Zyracki, C. Olguin, S. Tibbits and R.Raskar

    Nature/Scientific Reports, 4, 2014. 

​

9. Pose estimation using time-resolved inversion of diffuse light

    Dan Raviv, C. Barsi, N. Naik, M. Feigin and R. Raskar

    Optics Express, 22 (17), 2014. 

    Selected by the editors for the Virtual Journal on Biomedical Optics (VJBO), 2014.

​

10. Affine invariant geometry for non-rigid shapes

   Dan Raviv and R. Kimmel

   International journal of computer vision (IJCV), 111 (1), 2014.

​

11. Equi-affine invariant geometry for shape analysis

    Dan Raviv, A. M. Bronstein, M. M. Bronstein, D. Waismann, N. Sochen and R. Kimmel.  

   Journal of Mathematical Imaging and Vision (JMIV), 50 (1-2), 2014.

​

12. Locating and classifying fluorescent tags behind turbid layers non-invasively using sparsity-based time-resolved inversion

    G. Satat, C. Barsi, B. Heshmat, Dan Raviv and R. Raskar   

    Nature communications, 6, 2015.

​

13. Scale invariant metrics of volumetric datasets

    Dan Raviv, and R. Raskar

    SIAM Journal on Imaging Sciences, 8(1) (SIIMS), 2015.

​

14. All photons imaging through volumetric scattering

    G. Satat, B. Heshmat,  and R. Raskar      

   Nature/Scientific Reports, 2016

​

15. Locally Rigid Averaging (LRA): Expected geometrical mean from stretchable non-rigid observations

    Dan Raviv, E. Bayro-Corrochano and R. Raskar

    International Journal of Computer Vision (IJCV), 2017

​

16. Multi-velocity neural networks for facial expression recognition in videos

    O. Gupta, Dan Raviv and R. Raskar

    IEEE Transactions on Affective Computing, 2017. 

​

17. Illumination invariant  in Deep video gesture recognition

    O. Gupta,  and R. Raskar  

    Pattern Recognition, 2018.

​

18. MRZ code extraction from visa and passport documents using convolutional neural networks

     International Journal on Document Analysis and Recognition (IJDAR), 2021

    Y. Liu, H. James, O.Gupta and 

 

​

​

Conferences (full papers / peer review):

  1. Symmetries of non-rigid shapes 

Dan Raviv, A. M. Bronstein, M. M. Bronstein and R. Kimmel.

Proc. Workshop on Non-rigid Registration and Tracking (NRTL), 2007.      

Part of International Conference of Computer Vision (ICCV).

  1. Volumetric heat kernel signatures

Dan Raviv, A. M. Bronstein and M. M. Bronstein and R. Kimmel.

Proc. Workshop on 3D Object Retrieval, 2010.

  1. Diffusion symmetries of non-rigid shapes 

Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and G. Sapiro.

Proc. 3D Data Processing Visualization and Transmission (3DPVT), 2010.

  1. Affine-invariant diffusion geometry for the analysis of deformable 3D shapes

Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and N. Sochen.

Proc. IEEE Computer Vision and Pattern Recognition (CVPR), 2011.

  1. Hierarchical matching of non-rigid shapes

Dan Raviv, A.  Dubrovina, R. Kimmel 

Proc. Scale Space and Variational methods (SSVM), 2011.

  1. Affine-invariant Photometric Heat Kernel Signatures

A. Kovnastsky, Dan Raviv, M. M. Bronstein, A. M. Bronstein, R. Kimmel 

Proc. Eurographics workshop on 3D object retrieval (3DOR), 2012.

  1. Intrinsic Local Symmetries: A Computational Framework

C. Grushko, Dan Raviv and R. Kimmel

Proc. Eurographics workshop on 3D object retrieval (3DOR), 2012.

  1. Evaluating local contractions from large deformations using affine invariant spectral geometry

Dan Raviv, J. Lessick and R. Raskar

Statistical atlases and computational modeling of the heart (part of MICCAI), 2014.

9.     Cyclic Functional Mapping: Self-supervised correspondence between non-isometric deformable shapes.

D. Ginzburg and Dan Raviv

European Conference on Computer Vision (ECCV), 2020. Spotlight.

10.  It's All Around You: Range-Guided Cylindrical Coordinates for 3D Object Detection

M. Lavie and Dan Raviv

Proc. ICCV / Autonomous Vehicle Vision (AVVVision), 2021

  1. Occlusion guided scene flow estimation on 3D point clouds

B. Ouyang and 

Proc. CVPR / Workshop on Autonomous Driving (WAD), 2021

12.  FlowStep3D - Graph Unrolling for Self-Supervised Scene Flow Estimation

Y. Kittenplon and Dan Raviv

Proc. Conference on Computer Vision and Pattern Recognition (CVPR), 2021

  1. DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction

            Lang, D. Ginzburg, S. Avidan and Dan Raviv

            International Conference on 3D Vision (3DV) 2021

  1. Occlusion guided self-supervised scene flow estimation on 3D point clouds

B. Ouyang and 

            International Conference on 3D Vision (3DV) 2021

  1. Dual Geometric Graph Network (DG2N) Iterative network for deformable shape alignment

D. Ginzburg and Dan Raviv

International Conference on 3D Vision (3DV) 2021

 

Conferences(abstract/poster):

  1. Evidence based design of face masks for children through computerized 3D face analysis

M. Newhouse, A. Luder, A. Chalamish, Dan Raviv, R. Kimmel, and I. Amirav
            International Congress on Pediatric Pulmonology, 2012

Pediatric Respiratory Reviews, 2012.

  1. Locating fluorescence lifetimes behind turbid layers non-invasively using sprase, time-resolved inversion

G. Stat, C. Barsi, B. Heshmat, Dan Raviv and R. Raskar

CLEO: Science and Innovations, 2014.

  1. Imaging through thick turbid medium using time-resolved measurement

G. Stat, Dan Raviv, B. Heshmat, and R. Raskar

Computational Optical Sensing and Imaging, Imaging and Applied Optics. CT3F4, 2015.

  1. Deep video gesture recognition using illumination invariants

O. Gupta,  and R. Raskar  

BigVision, the 4th international workshop on large scale visual recognition and retrieval, 2016

  1. From non-rigid to null-space

Dan Raviv

IPAM: Geometry and Learning from Data in 3D and beyond: Shape analysis, 2019.

 

Book chapters

  1. Hierarchical matching of non-rigid shapes

Dan Raviv, A.  Dubrovina, R. Kimmel 

Proc. Scale Space and Variational methods. LNCS 6667, 2012.

  1. Equi-affine invariant geometries of articulated objects

Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and N. Sochen

Lectures notes in Computer Science. LNCS 7474, 2012. Presented in at Dagstuhl seminar no. 11261.

  1. Non-rigid shape correspondence using pointwise surface descriptors and metric structures

A. Dubrovina, Dan Raviv, and R. Kimmel

Innovations for Shape Analysis, Mathematics and Visualization 2013. Presented at Dagstuhl seminar no. 11142, 2011.

  1. Evaluating local contractions from large deformations using affine invariant spectral geometry

Dan Raviv, J. Lessick and R. Raskar

Statistical atlases and computational modeling of the heart (part of MICCAI), 2014.

  1. Computational Invariants for Curves and Surfaces

O. Halimi, , Y. Aflalo and R. Kimmel

Processing, Analyzing and Learning of Images, Shapes and Forms: Part 2, Volume 20, 2019.

 

Under review

  1. Skeleton-based typing style learning for person identification

L. Gelberg, D. Mendlovic and 

2.     Printing and scanning attach for image counter forensics

H. James, O. Gupta and Dan Raviv

3.     OCR graph features for manipulation detection in documents

H. James, O. Gupta and Dan Raviv

6.     Unsupervised Optical Flow Using Cost Function Unrolling

G. Lifshitz and Dan Raviv

7.     Geometry Enhancements from Visual Content: Going Beyond Ground Truth

L. Azaria and Dan Raviv

8.     Unsupervised Scale-Invariant Multi-Spectrum Shape Matching

I.K. Paz, D. Ginzburg and Dan Raviv

  1. Deep Weighted Consensus – Dense correspondence confidence maps for 3D shape registration

D. Ginzburg and 

Latest Publications

Journals

​

1.  Full and partial symmetries of non-rigid shapes 

     Dan Raviv, A. M. Bronstein, M. M. Bronstein and R. Kimmel.

     International Journal of Computer Vision (IJCV), 89 (1), 2009.

​

2. Affine-invariant geodesic geometry of deformable 3D shapes

     Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and N. Sochen.

     Computers & Graphics Journal, 35 (3), 2011.

     Also published in Proc. Shape Modeling International, 2011. 

​

3. Design of aerosol face masks for children using computerized 3D face analysis

     Amirav, A. Luder, A. Halamish, Dan Raviv, R. Kimmel and M. Newhouse

     Journal of Aerosol Medicine and Pulmonary drug Delivery, 27 (4), 2013.

 

4. Scale invariant geometry of non-rigid shape

     Y. Aflalo, R. Kimmel and Dan Raviv

     SIAM Journal on Imaging Sciences (SIIMS), 6 (3), 2013.

 

5.  Graph Isomorphisms and Automorphisms via Spectral Signatures

    Dan Raviv, R. Kimmel and Alfred. M. Bruckstein

    Transactions on Pattern analysis and Machine Intelligence (TPAMI), 35 (8), 2013.

 

6.  Geometric and photometric data fusion in non-rigid shape analysis

    Kovnastsky, Dan Raviv, M. M. Bronstein, A. M. Bronstein, R. Kimmel 

    Numerical Mathematics: Theory, Methods and Applications, 6 (1), 2013. 

 

7. Hierarchical matching of non-rigid shapes

    Dan Raviv, A.  Dubrovina , R. Kimmel

    Numerical Mathematics: Theory, Methods and Applications, 6 (1), 2013.

​

8. Active printed materials for complex self-evolving deformations

    Dan Raviv, W. Zhao, C. McKnelly, A. Papadopoulou, A. Kadambi, B. Shi, S. Hirsch, 

    D. Dikovski, M. Zyracki, C. Olguin, S. Tibbits and R.Raskar

    Nature/Scientific Reports, 4, 2014. 

​

9. Pose estimation using time-resolved inversion of diffuse light

    Dan Raviv, C. Barsi, N. Naik, M. Feigin and R. Raskar

    Optics Express, 22 (17), 2014. 

    Selected by the editors for the Virtual Journal on Biomedical Optics (VJBO), 2014.

​

10. Affine invariant geometry for non-rigid shapes

   Dan Raviv and R. Kimmel

   International journal of computer vision (IJCV), 111 (1), 2014.

​

11. Equi-affine invariant geometry for shape analysis

    Dan Raviv, A. M. Bronstein, M. M. Bronstein, D. Waismann, N. Sochen and R. Kimmel.  

   Journal of Mathematical Imaging and Vision (JMIV), 50 (1-2), 2014.

​

12. Locating and classifying fluorescent tags behind turbid layers non-invasively using sparsity-based time-resolved inversion

    G. Satat, C. Barsi, B. Heshmat, Dan Raviv and R. Raskar   

    Nature communications, 6, 2015.

​

13. Scale invariant metrics of volumetric datasets

    Dan Raviv, and R. Raskar

    SIAM Journal on Imaging Sciences, 8(1) (SIIMS), 2015.

​

14. All photons imaging through volumetric scattering

    G. Satat, B. Heshmat,  and R. Raskar      

   Nature/Scientific Reports, 2016

​

15. Locally Rigid Averaging (LRA): Expected geometrical mean from stretchable non-rigid observations

    Dan Raviv, E. Bayro-Corrochano and R. Raskar

    International Journal of Computer Vision (IJCV), 2017

​

16. Multi-velocity neural networks for facial expression recognition in videos

    O. Gupta, Dan Raviv and R. Raskar

    IEEE Transactions on Affective Computing, 2017. 

​

17. Illumination invariant  in Deep video gesture recognition

    O. Gupta,  and R. Raskar  

    Pattern Recognition, 2018.

​

18. MRZ code extraction from visa and passport documents using convolutional neural networks

     International Journal on Document Analysis and Recognition (IJDAR), 2021

    Y. Liu, H. James, O.Gupta and 

 

​

​

​

​

​

​

​

1. Symmetries of non-rigid shapes  

    Dan Raviv, A. M. Bronstein, M. M. Bronstein and R. Kimmel.

    Proc. Workshop on Non-rigid Registration and Tracking (NRTL), 2007.      

    Part of International Conference of Computer Vision (ICCV).

​

2. Volumetric heat kernel signatures

    Dan Raviv, A. M. Bronstein and M. M. Bronstein and R. Kimmel.

    Proc. Workshop on 3D Object Retrieval, 2010.

 

3. Diffusion symmetries of non-rigid shapes 

    Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and G. Sapiro.

    Proc. 3D Data Processing Visualization and Transmission (3DPVT), 2010.

 

4. Affine-invariant diffusion geometry for the analysis of deformable 3D shapes

    Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and N. Sochen.

    Proc. IEEE Computer Vision and Pattern Recognition (CVPR), 2011.

​

5. Hierarchical matching of non-rigid shapes. 

    Dan Raviv, A.  Dubrovina, R. Kimmel 

    Proc. Scale Space and Variational methods (SSVM), 2011.

​

6. Affine-invariant Photometric Heat Kernel Signatures

     A. Kovnastsky, Dan Raviv, M. M. Bronstein, A. M. Bronstein, R. Kimmel 

    Proc. Eurographics workshop on 3D object retrieval (3DOR), 2012.

​

7. Intrinsic Local Symmetries: A Computational Framework

    C. Grushko, Dan Raviv and R. Kimmel

    Proc. Eurographics workshop on 3D object retrieval (3DOR), 2012.

​

8. Evaluating local contractions from large deformations using affine invariant spectral geometry

    Dan Raviv, J. Lessick and R. Raskar

    Statistical atlases and computational modeling of the heart (part of MICCAI), 2014.

​

9. Cyclic Functional Mapping: Self-supervised correspondence between non-isometric deformable shapes.

    D. Ginzburg and Dan Raviv

    European Conference on Computer Vision (ECCV), 2020. Spotlight.

​

10. FlowStep3D: Model unrolling for self-supervised scene flow estimation

     Y. Kittenplon , Y. Eldar and Dan Raviv

     Proc. Conference on Computer Vision and Pattern Recognition (CVPR), 2021

​

11. It’s all around you: Range-guided cylindrical network for 3D object detection

      M. Lavie  and Dan Raviv

      Proc. ICCV / Autonomous Vehicle Vision (AVVVision), 2021

 

12. Occlusion guided scene flow estimation on 3D point clouds

      B. Ouyang and Dan Raviv

      Proc. CVPR / Workshop on Autonomous Driving (WAD), 2021

​

13. DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction

      Lang, D. Ginzburg , S. Avidan and Dan Raviv

      International Conference on 3D Vision (3DV) 2021

 

14. Occlusion guided self-supervised scene flow estimation on 3D point clouds

      B. Ouyang and Dan Raviv

      International Conference on 3D Vision (3DV) 2021

 

15. Dual Geometric Graph Network (DG2N) Iterative network for deformable shape alignment

      D. Ginzburg and Dan Raviv

      International Conference on 3D Vision (3DV) 2021

 

16. Skeleton-based type style learning for person identification

      L. Gelberg , D. Mendelovich and Dan Raviv

      xAI4Biometrics Workshop , WACV 2022

 

17. Deep confidence guided distance for 3D partial shape registration

      D. Ginzburg and Dan Raviv

     Association of the Advancement of Artificial Intelligence (AAAI) 2022

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​

 

1. Evidence based design of face masks for children through computerized 3D face analysis

    M. Newhouse, A. Luder, A. Chalamish, Dan Raviv, R. Kimmel, and I. Amirav
    International Congress on Pediatric Pulmonology, 2012

    Pediatric Respiratory Reviews, 2012.

​

2. Locating fluorescence lifetimes behind turbid layers non-invasively using sprase, time-resolved inversion

    G. Stat, C. Barsi, B. Heshmat, Dan Raviv and R. Raskar

    CLEO: Science and Innovations, 2014.

​

3.  Imaging through thick turbid medium using time-resolved measurement

     G. Stat, Dan Raviv, B. Heshmat, and R. Raskar

     Computational Optical Sensing and Imaging, Imaging and Applied Optics. CT3F4, 2015.

​

4.  Deep video gesture recognition using illumination invariants

    O. Gupta,  and R. Raskar  

    BigVision, the 4th international workshop on large scale visual recognition and retrieval, 2016

​

5. From non-rigid to null-space

    Dan Raviv

    IPAM: Geometry and Learning from Data in 3D and beyond: Shape analysis, 2019.

 

​

​

​

​

​

​

1. Hierarchical matching of non-rigid shapes

    Dan Raviv, A.  Dubrovina, R. Kimmel 

    Proc. Scale Space and Variational methods. LNCS 6667, 2012.

​

2. Equi-affine invariant geometries of articulated objects

    Dan Raviv, A. M. Bronstein, M. M. Bronstein, R. Kimmel and N. Sochen

    Lectures notes in Computer Science. LNCS 7474, 2012. Presented in at Dagstuhl seminar no. 11261.

​

3. Non-rigid shape correspondence using pointwise surface descriptors and metric structures

    A. Dubrovina, Dan Raviv, and R. Kimmel

    Innovations for Shape Analysis, Mathematics and Visualization 2013. Presented at Dagstuhl seminar no. 11142, 2011.

 

4. Evaluating local contractions from large deformations using affine invariant spectral geometry

    Dan Raviv, J. Lessick and R. Raskar

    Statistical atlases and computational modeling of the heart (part of MICCAI), 2014.

​

5. Computational Invariants for Curves and Surfaces

    O. Halimi, , Y. Aflalo and R. Kimmel

    Processing, Analyzing and Learning of Images, Shapes and Forms: Part 2, Volume 20, 2019.

 

Conferences Abstract

Conferences peer reviewed

Book chapters

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