Vladimir D. Luchinskiy

Papers

Total Citations

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About

Vladimir D. Luchinskiy is a leading researcher in autonomous vehicle perception, specializing in 3D LiDAR point cloud segmentation and domain adaptation. His most influential work, "DAPS3D: Domain Adaptive Projective Segmentation of 3D LiDAR Point Clouds" (2023, 13 citations), tackles a critical challenge in self-driving technology: the inability of segmentation neural networks to generalize across different LiDAR sensors or environmental conditions. By developing a novel projective segmentation framework that bridges domain gaps, Luchinskiy enables more robust and reliable scene understanding—identifying roads, buildings, pedestrians, and vehicles—without requiring costly retraining for every new sensor setup. This work directly addresses the limitations of traditional point- and voxel-based networks, which struggle with sparse and irregular LiDAR data. Beyond DAPS3D, his research advances the practical deployment of autonomous systems by improving how machines interpret complex 3D environments. With growing citation impact, Luchinskiy is recognized for pushing the boundaries of domain-adaptive perception, making autonomous vehicles safer and more adaptable to real-world conditions.