activity
20242026
most citedcadrille: Multi-modal CAD Reconstruction with Reinforcement Learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20261 cited

cadrille: Multi-modal CAD Reconstruction with Reinforcement Learning

Maksim Kolodiazhnyi, Denis Tarasov, Dmitrii Zhemchuzhnikov +6

Computer-Aided Design (CAD) plays a central role in engineering and manufacturing, making it possible to create precise and editable 3D models. Using a variety of sensor or user-pr…

cs.CV2026

Z3D: Zero-Shot 3D Visual Grounding from Images

Nikita Drozdov, Andrey Lemeshko, Nikita Gavrilov +3

3D visual grounding (3DVG) aims to localize objects in a 3D scene based on natural language queries. In this work, we explore zero-shot 3DVG from multi-view images alone, without r…

cs.CV2025

Zoo3D: Zero-Shot 3D Object Detection at Scene Level

Andrey Lemeshko, Bulat Gabdullin, Nikita Drozdov +3

3D object detection is fundamental for spatial understanding. Real-world environments demand models capable of recognizing diverse, previously unseen objects, which remains a major…

cs.CV2025

TUN3D: Towards Real-World Scene Understanding from Unposed Images

Anton Konushin, Nikita Drozdov, Bulat Gabdullin +4

Layout estimation and 3D object detection are two fundamental tasks in indoor scene understanding. When combined, they enable the creation of a compact yet semantically rich spatia…

cs.CV2024

UniDet3D: Multi-dataset Indoor 3D Object Detection

Maksim Kolodiazhnyi, Anna Vorontsova, Matvey Skripkin +2

Growing customer demand for smart solutions in robotics and augmented reality has attracted considerable attention to 3D object detection from point clouds. Yet, existing indoor da…