Vladislav Pyatov — accepted AI-conference papers

2026

CADFS: A Big CAD Program Dataset and Framework for Computer-Aided Design with Large Language Models

Vladislav Pyatov, Gleb Bobrovskikh, Saveliy Galochkin, Nikita Boldyrev, Oleg Voynov, Alexander Filippov +3

CVPR 2026

We introduce CADFS, a data-centric framework that enables large vision-language models to generate complex CAD design histories. Existing generative CAD systems are restricted to sketch-extrude operations due to simplified representations and limited datasets. We address this by introducing a Featur

Cited by 3 Source ↗code ↗Scholar ↗

2024

GSLoc: Visual Localization with 3D Gaussian Splatting

Kazii Botashev, Vladislav Pyatov, Gonzalo Ferrer, Stamatios Lefkimmiatis

IROS 2024poster

We present GSLoc: a new visual localization method that performs dense camera alignment using 3D Gaussian Splatting as a map representation of the scene. GSLoc backpropagates pose gradients over the rendering pipeline to align the rendered and target images, while it adopts a coarse-to-fine strategy…

Cited by 5 Source ↗Scholar ↗

2024

Robust Two-View Geometry Estimation with Implicit Differentiation

Vladislav Pyatov, Iaroslav Koshelev, Stamatios Lefkimmiatis

IROS 2024poster

We present a novel two-view geometry estimation framework which is based on a differentiable robust loss function fitting. We propose to treat the robust fundamental matrix estimation as an implicit layer, which allows us to avoid backpropagation through time and significantly improves the numerical…

Cited by 0 Source ↗code ↗Scholar ↗