1 citations · 2 across the 6 of their papers we have counts for
6 papers
Unified Sensor Simulation for Autonomous Driving
Nikolay Patakin, Arsenii Shirokov, Anton Konushin +1
In this work, we introduce \textbf{XSIM}, a sensor simulation framework for autonomous driving. XSIM extends 3DGUT splatting with a generalized rolling-shutter modeling tailored fo…
Visual Implicit Geometry Transformer for Autonomous Driving
Arsenii Shirokov, Mikhail Kuznetsov, Danila Stepochkin +5
We introduce the Visual Implicit Geometry Transformer (ViGT), an autonomous driving geometric model that estimates continuous 3D occupancy fields from surround-view camera rigs. Vi…
DepthART: Monocular Depth Estimation as Autoregressive Refinement Task
Bulat Gabdullin, Nina Konovalova, Nikolay Patakin +2
Monocular depth estimation has seen significant advances through discriminative approaches, yet their performance remains constrained by the limitations of training datasets. While…
A3D: Does Diffusion Dream about 3D Alignment?
Savva Ignatyev, Nina Konovalova, Daniil Selikhanovych +9
We tackle the problem of text-driven 3D generation from a geometry alignment perspective. Given a set of text prompts, we aim to generate a collection of objects with semantically…
Single-Stage 3D Geometry-Preserving Depth Estimation Model Training on Dataset Mixtures with Uncalibrated Stereo Data
Nikolay Patakin, Mikhail Romanov, Anna Vorontsova +2
Nowadays, robotics, AR, and 3D modeling applications attract considerable attention to single-view depth estimation (SVDE) as it allows estimating scene geometry from a single RGB…
Independent Component Alignment for Multi-Task Learning
Dmitry Senushkin, Nikolay Patakin, Arseny Kuznetsov +1
In a multi-task learning (MTL) setting, a single model is trained to tackle a diverse set of tasks jointly. Despite rapid progress in the field, MTL remains challenging due to opti…