Tomas Pajdla

 

Associate Professor & Distinguished Researcher, Leader of AAG Group

AAG - Applied Algebra & Geometry Group

Czech Institute of Informatics, Robotics and Cybernetics

Czech Technical University in Prague

Visiting Associate Professor

National Institute of Informatics, Tokyo

 pajdla@cvut.cz  pajdla       

Get to us: Office B-638 CIIRC Building B Jugoslavkych partyzanu 3, 16000 Prague, Czechia

 

 

News

Research

ResTopics

Software

Projects

 

 

 

 

 

2018 June
3 Papers @ CVPR 2018
2017 December

AC of ECCV 2018

2017 September

Continental project

2017 September 
PC of 3DV 2018

see past news

Interests  

Computer Vision, Machine Learning, Robotics, Geometry, Algebra, Optimization

Papers  

See my ScholarDBLP & arXiv

Talks  

Algebraic Geometry & 3D Reconstruction @ ISPRS 2016, Solving Minimal Problems in Computer Vision Tutorial @ ICCV 2015,  Omnidirectional Vision Course @ ICCV 2003, Stereo Geometries of Non-central Cameras 2001   

Teaching  

Geometry of Computer Vision and Computer Graphics (CTU in Prague), Advanced Robotics (CTU in Prague), Geometry of Computer Vision (Charles University in Prague), Geometry of Computer Vision (Ukrainian Catholic University in Lvov)

Links  

CVF, CMP, CIIRC Assembly, INRIA Willow, MAGIK Eye

 

Alumni

P. Trutman MSc 2018 (CTU Prague)
P Gronat PhD 2017 (AVAST)

O Rybkin Bc 2017 (U Penn)

J Heller PhD 2016 (MAGIK Eye)

F Srajer MSc 2016 (ETH Zurich)

V Smutny PhD 2016 (CTU Prague)

M. Polic MSc 2015 (CTU Prague)

M Jancosek PhD 2015 (Capturing Reality)

Z Kukelova PhD 2013 (Microsoft Resrch)

M Bujnak PhD 2013 (Capturing Reality)

M Havlena PhD 2012 (ETH Zurich)

C Albl MSc 2011 (CTU Prague)

J Smisek MSc 2011 (University Delft)

J Knopp MSc 2009 (KU Leuven)

T Ehlgen PhD 2008 (Bosch)

H Bakstein PhD 2006 (EU Patent Office)

B Micusik PhD 2004 (Stanford University)

D Martinec PhD 2003 (Microsoft)

J Sivic MSc 2002 (Oxford University)

O Chum MSc 2001 (CTU in Prague)

R Horcik MSc 2001 (CTU in Prague)

T Svoboda PhD 2000 (ETH Zurich)

 

Research

Beyond Gröbner Bases: Basis Selection for Minimal Solvers

V Larsson, M Oskarsson, K Åström, A Wallis, Z Kukelova, T Pajdla
CVPR 2018 pdf | arXiv

InLoc: Indoor Visual Localization with Dense Matching and View Synthesis

H Taira, M Okutomi, T Sattler, M Cimpoi, M Pollefeys, J Sivic, T Pajdla, A Torii

CVPR 2018 pdf | arXiv | Project page | bib

Benchmarking 6DOF Urban Visual Localization in Changing Conditions

T Sattler, W Maddern, C Toft, A Torii, L Hammarstrand, E Stenborg, D Safari, M Okutomi, M Pollefeys, J Sivic, F Kahl, T Pajdla
CVPR 2018 pdf |
arXiv | Project page

24/7 Place Recognition by View Synthesis
A Torii, R Arandjelovic, J Sivic, M Okutomi, T Pajdla
IEEE TPAMI 2018 pdf | CVPR 2015 pdf | Project page+data+code

 

NetVLAD: CNN architecture for weakly supervised place recognition

R Arandjelovic, P Gronat, A Torii, T Pajdla and J Sivic

IEEE PAMI 2018 pdf | CVPR 2016 pdf | Project page (oral) | video

 

Camera Uncertainty Computation in Large 3D Reconstruction

M Polic, T Pajdla
3DV 2017 pdf | Project page

Nautilus: recovering regional symmetry transformations for image editing

M Lukac, D Sykora, K Sunkavalli, E Shechtman, O Jamriska, N Carr, T Pajdla

SIGGRAPH 2017 | ACM TOG Journal PDF | Project page

 

Are Large-Scale 3D Models Really Necessary for Accurate Visual Localization?

T Sattler, A Torii, J Sivic, M Pollefeys, H Taira, M Okutomi, T Pajdla

CVPR 2017 | pdf | Project page

 

On the Two-View Geometry of Unsynchronized Cameras

C Albl, Z Kukelova, A Fitzgibbon, J Heller, M Smid, T Pajdla

CVPR 2017 | pdf | Supplementary

 

A clever elimination strategy for efficient minimal solvers

Z Kukelova, J Kileel, B Sturmfels, T Pajdla

CVPR 2017 | pdf | Supplementary | arXiv

 

Distortion varieties

J Kileel, Z Kukelova, T Pajdla, B Sturmfels

Foundations of Computational Mathematics | arXiv

 

Degeneracies in rolling shutter SfM

C Albl, A Sugimoto, T Pajdla

ECCV 2016 | LNCS | pdf

 

Globally optimal hand-eye calibration using branch-and-bound

J Heller, M Havlena, T Pajdla

IEEE TPAMI 2016 | pdf

Learning and Calibrating Per-Location Classifiers for Visual Place Recognition

P Gronat, J Sivic, G Obozinski, T Pajdla

IJCV 2016 pdf | CVPR 2013 pdf

 

GpoSolver: a Matlab/C++ toolbox for global polynomial optimization

J Heller, T Pajdla

Optimization Methods and Software 2016 | pdf | Software

 

 

Software from AAG

Automatic Generator of Minimal Solvers

YASM – Yet Another SfM

CMP SfM Webservice
CMPMVS  – MV Stereo (
AliceVision)

GpoSolver – Global Polynom Optimization

radhomo-0.1 – Rad Dist Homogrphy [pdf]

F10-0.1 – Rad Relative Pose [pdf]

bbhec – BB Hand-Eye Optimization

mpherwc – Hand-Eye & R-W Cal [pdf]

minhec – Hand-Eye Cal Minimal [pdf]

polyopt  –  Polynom Opt by SDP Relax

TE-inversion – Uncertainty propag in SfM

 

 

Projects

2017  

2017 IMPACT Project (EU & MSMT)

2017  & CTU Research Lab

2016 LADIO Project (H2020 EU)

 

Student Research Topics

Research topics for PhD, MSc and Bc students.

 

3D Scene Reconstruction from Images

3D scene reconstruction from images is a fundamental problem of computer vision. It finds many applications in industry ranging from autonomous driving to movie special effects. The topic is best for students with interest in algorithms, experimental work, and engineering of really working systems.
Algebraic Methods in Computer Vision and Robotics

Algebraic techniques have proved very useful in solving difficult problems in geometry of computer vision. We will aim at studying more advanced elements of algebraic geometry and applying them to real engineering problems. The topic is best for students with interest in applied mathematics.
Image-based Scene Recognition and Visual Localization

Visual scene recognition and image based localization is an important problem in computer vision and machine learning. We will aim developing new approaches to place representation and its search. The topic is suitable for students with interest computer vision and machine learning applied to real engineering problems.

Polynomial Optimization in Computer Vision and Robotics

Polynomial optimization techniques proved very useful in solving interesting problems in geometry of computer vision and robotics. We will aim at studying more polynomial optimization techniques and applying them in computer vision and robotics. The topic is suitable for students with interest in applied mathematics but used on real engineering problems.

 

 

Past News

2017 July J Heller received CSKI Prize 4 his PhD, 2017 July 3 Papers @ CVPR 2017, 2017 June IMPACT project with INRIA started, 2017 May MAGIK Eye – CTU Common Lab founded, 2016 November PC of ACCV 2020, June 2016 3 papers @ CVPR 2016, June 2015 3 papers @ CVPR 2015, January 2015 LADIO EU Project starts.

 

©Tomas Pajdla 2017-2018