Tomáš Souček

PhD Candidate | AI Research Lead

Czech Technical University
Prague, Jugoslávských partyzánů 3, B-636a
tomas (dot) soucek (at) cvut.cz

SANEZOO EUROPE
Brno, Vlněna 7
tomass (at) sanezoo.com

github     linkedin     scholar

I am a final-year PhD student at IMPACT (CTU/CIIRC), working under the supervision of Josef Šivic (IMPACT), Ivan Laptev (Inria), and Dima Damen (University of Bristol, Deepmind). I also lead a team of researchers, engineers, and robotics experts responsible for developing a universal bin-picking solution at SANEZOO.

Previously, I worked as a Senior Researcher at Avast AI lab, working with large transformer neural networks. I got a Master's degree in Artificial intelligence at Charles University. I also spent three months as a Visiting Researcher at the University of Bristol.

Selected Publications

T. Souček, D. Damen, M. Wray, I. Laptev, and J. Šivic
GenHowTo: Learning to Generate Actions and State Transformations from Instructional Videos
CVPR'24
[website] [paper] [code]
T. Souček, JB. Alayrac, A. Miech, I. Laptev, and J. Šivic
Multi-Task Learning of Object States and State-Modifying Actions from Web Videos
TPAMI'24
[website] [paper] [code]
T. Souček, JB. Alayrac, A. Miech, I. Laptev, and J. Šivic
Look for the Change: Learning Object States and State-Modifying Actions from Untrimmed Web Videos
CVPR'22
[website] [paper] [code] [dataset]
T. Souček, and J. Lokoč
TransNet V2: An effective deep network architecture for fast shot transition detection
Arxiv'20
[paper] [code]
J. Lokoč, G. Kovalčík, T. Souček, J. Moravec, and P. Čech
A Framework for Effective Known-item Search in Video
ACM MM'19
[paper]

See the list of all publications on Google Scholar.

Other Selected Projects

Fast incident detection by detecting anomalies in user requests
Project leader at Avast
Modeling user requests in time as a probability distribution of distributions in high dimensional space of Transformer-based neural networks.
Autoregressive action-conditioned 3D human motion synthesis using latent discrete codes
Thesis of Jan Waltl, co-advised with J. Šivic
[text]
Measuring advertisement reach using smart glasses
Lead investigator for a joint project of Charles University and MEDIAN (media and public opinion research agency)
Ad detection and tracking in videos from smart glasses for automatically measuring ad reach.

Miscellaneous

Reviewer for CVPR, ICCV, ECCV, SIGGRAPH, and others.

Currently supervising two master students at Masaryk University.

Teaching Assistant for Deep Learning and Intro to Algorithms.