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Weak-to-Strong 3D Object Detection with X-Ray Distillation
P. 15055–15064.
IEEE, 2026.
Added: July 13, 2026
Абрамов А. С., Chernyshev V. L., Mikhaylets E. et al., / Series Social Science Research Network "Social Science Research Network". 2025.
Computer vision is one of the most relevant modern research areas with broad practical applications. However, traditional solutions based on deep learning have signicant limitations and can be misleading. Topological data analysis, on the other hand, is a modern approach to solving similar problems using mathematically deterministic methods of algebraic topology that reduce the risk ...
Added: September 23, 2025
Gambashidze A., Dadukin A., Golyadkin M. et al., , in: Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24).: International Joint Conferences on Artificial Intelligence, 2024. Ch. 1001 P. 8653–8656.
This paper demonstrates a novel method for LiDAR-based 3D object detection, addressing major field challenges: sparsity and occlusion. Our approach leverages temporal point cloud sequences to generate frames that provide comprehensive views of objects from multiple angles. To address the challenge of generating these frames in real-time, we employ Knowledge Distillation within a Teacher-Student framework, ...
Added: April 29, 2025
Соловьёв Р. А., Габрушева Т., Калинин А., Computers in Biology and Medicine 2022 Vol. 141 P. 105–113
Adequate blood supply is critical for normal brain function. Brain vasculature dysfunctions, including stalled blood flow in cerebral capillaries, are associated with cognitive decline and pathogenesis in Alzheimer's disease. Recent advances in imaging technology enabled generation of high-quality 3D images that can be used to visualize stalled blood vessels. However, localization of stalled vessels in ...
Added: January 15, 2025
Соловьёв Р. А., Габрушева Т., Ванг В., Image and Vision Computing 2021 Vol. 107 P. 104117–0
We present a novel method for combining predictions in ensembles of different object detection models: weighted boxes fusion. This method significantly improves the quality of the fused predicted rectangles for an ensemble.
We tested the method on several datasets and evaluated it in the context of the Open Images and COCO Object Detection challenges. It helped ...
Added: January 15, 2025
Hamplová A., Lyavdansky A., Novák T. et al., CMES - Computer Modeling in Engineering and Sciences 2024 Vol. 140 No. 3 P. 2869–2889
This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions, employing two state-of-the-art deep learning algorithms, namely YOLOv8 and Roboflow 3.0. The goal is to contribute to the preservation and understanding of historical texts, showcasing the potential of modern deep learning methods in archaeological research. Our research culminates in several ...
Added: July 17, 2024
Cham: Springer, 2024.
This book constitutes revised selected papers from the thoroughly refereed proceedings of the 11th International Conference on Analysis of Images, Social Networks and Texts, AIST 2023, held in Yerevan, Armenia, during September 28-30, 2023.
The 24 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections ...
Added: March 25, 2024
Maksim Golyadkin, Alexander Gambashidze, Nurgaliev I. et al., IEEE Access 2024 Vol. 12 P. 3805–3814
In response to the growing demand for 3D object detection in applications such as autonomous driving, robotics, and augmented reality, this work focuses on the evaluation of semi-supervised learning approaches for point cloud data. The point cloud representation provides reliable and consistent observations regardless of lighting conditions, thanks to advances in LiDAR sensors. Data annotation ...
Added: March 13, 2024
Nikita Starodubcev, Dmitry Baranchuk, Artem Fedorov et al., , in: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).: IEEE, 2024. P. 9275–9285.
Knowledge distillation methods have recently shown to be a promising direction to speedup the synthesis of large-scale diffusion models by requiring only a few inference steps. While several powerful distillation methods were recently proposed, the overall quality of student samples is typically lower compared to the teacher ones, which hinders their practical usage. In this ...
Added: March 5, 2024
IEEE, 2024.
Added: March 5, 2024
Zagitov A., Chebotareva E., Toschev A. et al., Computer Optics 2024 Vol. 48 No. 2 P. 242–252
A computer vision based real-time object detection on low-power devices is economically attractive, yet a technically challenging task. The paper presents results of benchmarks on popular deep neural network models, which are often used for this task. The results of experiments provide insights into trade-offs between accuracy, speed, and computational efficiency of MobileNetV2 SSD, CenterNet ...
Added: February 25, 2024