Computer vision systems
Algorithms for analyzing images, video, objects, scenes and visual patterns.
STATANLY R&D
R&D projects and research
In 2024–2025, company employees published more than 80 scientific papers and research works in Russian and international journals and took part in dozens of scientific conferences in Russia and Europe.
RESEARCH AREAS
Main research topics
The main research topics are related to developing algorithms for automated construction of machine learning models. Our research is conducted in the following areas:
Large language models
Research in language models, text processing and knowledge representation.
Generative neural networks
Generative models for images, vector graphics, text and multimodal data.
Automated machine learning
Methods for automated construction, selection and optimization of machine learning models.
VLM (Vision Language Models)
Multimodal models that connect visual information and natural language.
Anomaly detection in data
Methods for finding unusual objects, events, deviations and hidden structures in data.
Natural language processing
Text analysis, entity extraction, semantic search and language data processing.
Information retrieval systems
Search, ranking, matching and work with large data corpora.
Data segmentation
Methods for identifying structures, classes, regions and semantic fragments in data.
Search for hidden patterns in data
Analysis of latent connections, dependencies and recurring structures in complex datasets.
SCIENTIFIC SCHOOL
Connection with ITMO research activity
Most of our developments in data analysis and machine learning are closely connected with scientific work conducted at the Faculty of Information Technologies and Programming of ITMO University in Saint Petersburg. Our team members include young scientists, university research laboratory staff and participants in research projects implemented jointly with leading Russian and international institutes. We are proud that our technologies and products are developed at the intersection of mathematics, programming and big data visualization and find use in different areas of everyday human activity.
The research is connected with scientific activity at the Faculty of Information Technologies and Programming of ITMO University.
The team includes young scientists and employees of university research laboratories.
Research projects are implemented jointly with leading Russian and international institutes.
Works are published in Russian and international journals, and results are presented at scientific conferences.
PUBLICATIONS
Selected research papers
Our scientific works are published in peer-reviewed journals in Russia and abroad.
Jarsky I., Treschev A., Shalamov V., Efimova V. Advancements in Vector Graphics Generation for Music Cover Art. Communications in Computer and Information Science. 2026. Vol. 2548. pp. 356–372.. doi: 10.1007/978-3-032-07623-6_19
Kasai S., Stumpf S., Zabashta A., Efimova V. Enhanced Class-Expertise Weighted Aggregation. Proceedings of the 21st International Conference on Computer Vision Theory and Applications. 2026. Vol. 1. pp. 671-678.. doi: 10.5220/0014621700004084
Yakovenko A., Bessonnitsyn E., Efimova V., Zaslavskiy M. Language-Specific Adaptation Strategies for Speaker Recognition Using MobileNet. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2026. Vol. 16187. pp. 322–332.. doi: 10.1007/978-3-032-07956-5_23
Bazhenov E., Kasai S., Shalamov V., Efimova V. GenPlan: Generation Vector Residential Plans Based on the Textual Description. Proceedings of the 21st International Conference on Computer Vision Theory and Applications. 2026. Vol. 3. pp. 283-290.. doi: 10.5220/0014238300004084
Bazhenov E.A., Kasai S.A., Shalamov V.V., Efimova V.A. Text-to-Vector Conversion for Residential Plan Design. arXiv.org [база препринтов]. 2026.
Малашенко Б.Т., Жарский И.А., Ефимова В.А. Leveraging Large Language Models For Scalable Vector Graphics Processing: A Review. Записки научных семинаров Санкт-Петербургского отделения Математического института им. В.А.Стеклова РАН. 2025. Т. 546. С. 59-80.
Jarsky I., Treschev A., Shalamov V., Efimova V. Advancements in Vector Graphics Generation for Music Cover Art. Communications in Computer and Information Science. 2026. Vol. 2548. pp. 356–372.. doi: 10.1007/978-3-032-07623-6_19
Kasai S., Stumpf S., Zabashta A., Efimova V. Enhanced Class-Expertise Weighted Aggregation. Proceedings of the 21st International Conference on Computer Vision Theory and Applications. 2026. Vol. 1. pp. 671-678.. doi: 10.5220/0014621700004084
Yakovenko A., Bessonnitsyn E., Efimova V., Zaslavskiy M. Language-Specific Adaptation Strategies for Speaker Recognition Using MobileNet. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2026. Vol. 16187. pp. 322–332.. doi: 10.1007/978-3-032-07956-5_23
Bazhenov E., Kasai S., Shalamov V., Efimova V. GenPlan: Generation Vector Residential Plans Based on the Textual Description. Proceedings of the 21st International Conference on Computer Vision Theory and Applications. 2026. Vol. 3. pp. 283-290.. doi: 10.5220/0014238300004084
Bazhenov E.A., Kasai S.A., Shalamov V.V., Efimova V.A. Text-to-Vector Conversion for Residential Plan Design. arXiv.org [база препринтов]. 2026.
Малашенко Б.Т., Жарский И.А., Ефимова В.А. Leveraging Large Language Models For Scalable Vector Graphics Processing: A Review. Записки научных семинаров Санкт-Петербургского отделения Математического института им. В.А.Стеклова РАН. 2025. Т. 546. С. 59-80.
Prokopov E., Usacheva D., Rumiantceva M., Efimova V. Weak Segmentation and Unsupervised Evaluation: Application to Froth Flotation Images. Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 2025. Vol. 3. pp. 500-507.. doi: 10.5220/0013181100003912
Jarsky I., Kuzin M., Efimova V., Shalamov V., Filchenkov A. VectorWeaver: Transformers-Based Diffusion Model for Vector Graphics Generation. Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 2025. Vol. 2. pp. 184-195.. doi: 10.5220/0013185100003912
Brykin G., Efimova V. ReactSR: Efficient Real-World Super-Resolution Application in a Single Floppy Disk. Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 2025. Vol. 3. pp. 483-490.. doi: 10.5220/0013175800003912
Saitov I., Filchenkov A. Recognition of Vehicle Country from License Plate Image based on Siamese Network Model with Triplet Loss Function and Negative Sampling Technique. CVCI proceedings. 2024. pp. TBD.
Baturina X., Shalamov V., Muravyov S., Filchenkov A. Mutation Management for Evolutionary Small-Moves Approach in Pickup and Delivery Problem. Procedia Computer Science. 2023. Vol. 229. pp. 109-118.
Saitov I., Filchenkov A. CIS Multilingual License Plate Detection and Recognition Based on Convolutional and Transformer Neural Networks. Procedia Computer Science. 2023. Vol. 229. pp. 149-157.
Useinov L.V., Efimova V.A., Muravyov S.B. Image Augmentation for Object Detection and Segmentation with Diffusion Models. Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. 2024. Vol. 2. pp. 812-820.
Timofeenko B., Efimova V., Filchenkov A. Vector graphics generation with LLMs: approaches and models. Записки научных семинаров Санкт-Петербургского отделения Математического института им. В.А.Стеклова РАН. 2023. Vol. 530. pp. 24-37.
Дзюба М.О., Жарский И.А., Ефимова В.А., Фильченков А.А. Image vectorization: a review [Векторизация изображений: обзор]. Записки научных семинаров Санкт-Петербургского отделения Математического института им. В.А.Стеклова РАН. 2023. Т. 530. С. 6-23.
Тимофеенко Б.А., Фильченков А.А., Ефимова В.А. Generation of vector graphics with ChatGPT. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2023. Vol. 13982.
Moskovskaya E., Chebotareva O., Efimova V., Muravyov S. Predicting dataset size for neural network fine-tuning with a given quality in object detection task. Procedia Computer Science. 2023. Vol. 229. pp. 158-167.
Шаламов В.В., Ефимова В.А., Фильченков А.А. Перевод нейронной сети в векторное представление. Современная наука: актуальные проблемы теории и практики. Серия: Естественные и технические науки. 2022. № 10. С. 159-162.
Ефимова В.А. Автоматическое определение места действия текста. Современная наука: актуальные проблемы теории и практики. Серия: Естественные и технические науки. 2022. № 10. С. 76-79.
Chizhikov D., Efimova V., Shalamov V., Filchenkov A. Inferring Image Background from Text Description. Communications in Computer and Information Science. 2022. Vol. 1731. pp. 1-13.
Efimova V., Shalamov V., Filchenkov A. First Describe, Then Depict: Generating Covers for Music and Books via Extracting Keywords: This paper presents two methods to generate high resolution uncopyrighted book covers or music album covers. ACM International Conference Proceeding Series. 2022. pp. 734-739.
Efimova V., Jarsky I., Bizyaev I., Filchenkov A. Conditional Vector Graphics Generation for Music Cover Images. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2022. pp. 2205.07301.
Efimova V., Filchenkov A. Text-based sequential image generation. Proceedings of SPIE. 2022. Vol. 12084. pp. 120840H.
Shalamov V., Efimova V., Filchenkov A. Faster Hyperparameter Optimization via Finding Minimal Regions in Random Forest Regressor. Procedia Computer Science. 2022. Vol. 212. pp. 378-386.
Efimova V., Fedotov L., Shalamov V., Filchenkov A. Advertisement Replacement in Video. Proceedings of SPIE. 2022. Vol. 12084. pp. 120840U.
Zabashta A., Smetannikov I., Filchenkov A. Rank aggregation algorithm selection meets feature selection [MLDM 2016]
Efimova V., Filchenkov A., Shalyto A. Reinforcement-based Simultaneous Algorithm and its Hyperparameters Selection [AWRL@ACML 2016]
A. Filchenkov, A. Pendryak Datasets Meta-Feature Description for Recommending Feature Selection Algorithm
Filchenkov A., Khanzhina N., Tsai A., Smetannikov I. Regularization of Autoencoders for Bank Client Profiling Based on Financial Transactions. Risks. 2021. Vol. 9. No. 3. pp. 54.
Filchenkov A., Krylov D.P., Khanzhina N., Zabashta A., Поляков С. Improving Multimodal Data Labeling with Deep Active Learning for Post Classi cation in Social Networks. ICMR. 2021. pp. 1-14.
Yang Q., Farseev A., Filchenkov A. Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling. ICDAR '21: Proceedings of the 2021 on Intelligent Cross-Data Analysis and Retrieval Workshop. 2021. pp. 8.
Farseev A., Yang Q., Filchenkov A., Lepikhin K., Chu-Farseeva Y., Loo D. SoMin.ai: Personality-Driven Content Generation Platform. 14th ACM International Conference on Web Search and Data Mining, WSDM 2021. 2021. pp. 890-893.
Asadulaev A., Kuznetcov I.S., Stein G., Filchenkov A. Exploring and Exploiting Conditioning of Reinforcement Learning Agents. IEEE Access. 2020. Vol. 8. pp. 211951-211960.
Asadulaev A., Stein G., Filchenkov A. Transgenerators. ACM International Conference Proceeding Series. 2020. pp. 3446417.
Efimova V., Shalamov V., Filchenkov A. Synthetic Dataset Generation for Text Recognition with Generative Adversarial Networks. Proceedings of SPIE. 2020. Vol. 11433. pp. 1143315.
Muravyov S., Filchenkov A. A Cloud-based Network of 3D Objects for Robust Grasp Planning. ACM International Conference Proceeding Series. 2020. pp. 99-105.
Khanzhina N., Slepkova N.D., Filchenkov A. Synthetic images generation for text detection and recognition in the wild. Proceedings of SPIE. 2020. Vol. 11433. pp. 1143312.
Viuginov N., Grachev P., Filchenkov A. A Machine Learning Based Plagiarism Detection In Source Code. ACM International Conference Proceeding Series. 2020. pp. 3446420.
Kochetov K., Filchenkov A. Generative Adversarial Networks for Respiratory Sound Augmentation. ACM International Conference Proceeding Series. 2020. pp. 106-111.
Muravyov S., Antipov D., Buzdalova A., Filchenkov A. Efficient Computation Of Fitness Function For Evolutionary Clustering. Mendel. 2019. Vol. 25. No. 1. pp. 87-94.
Oreshin S., Filchenkov A., Petrusha P., Krasheninnikov E., Panfilov A., Glukhov I., Kaliberda Y., Masalskiy D., Serdyukov A., Kazakovtsev V.L., Khlopotov M., Podolenchuk T., Smetannikov I., Kozlova D. Implementing a Machine Learning Approach to Predicting Students' Academic Outcomes. ACM International Conference Proceeding Series. 2020. pp. 78-83.
COLLABORATION
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The team’s scientific and research activity underlies the development of STATANLY technologies at the intersection of mathematics, programming, machine learning and big data visualization.