9 citations · 16 across the 6 of their papers we have counts for
9 papers
NAMVIS: Next-Scale Autoregressive Multi-View Image Synthesis
Ramil Khafizov, Ilya Statsenko, Ruslan Rakhimov +3
Sparse-view novel view synthesis is a central problem in 3D content creation, but diffusion-based approaches remain limited by iterative denoising, making multi-view generation exp…
G-CUT3R: Guided 3D Reconstruction with Camera and Depth Prior Integration
Ramil Khafizov, Artem Komarichev, Ruslan Rakhimov +2
We introduce G-CUT3R, a novel feed-forward approach for guided 3D scene reconstruction that enhances the CUT3R model by integrating prior information. Unlike existing feed-forward…
T-3DGS: Removing Transient Objects for 3D Scene Reconstruction
Alexander Markin, Vadim Pryadilshchikov, Artem Komarichev +3
Transient objects in video sequences can significantly degrade the quality of 3D scene reconstructions. To address this challenge, we propose T-3DGS, a novel framework that robustl…
Multi-NeuS: 3D Head Portraits from Single Image with Neural Implicit Functions
Egor Burkov, Ruslan Rakhimov, Aleksandr Safin +2
We present an approach for the reconstruction of textured 3D meshes of human heads from one or few views. Since such few-shot reconstruction is underconstrained, it requires prior…
NPBG++: Accelerating Neural Point-Based Graphics
Ruslan Rakhimov, Andrei-Timotei Ardelean, Victor Lempitsky +1
We present a new system (NPBG++) for the novel view synthesis (NVS) task that achieves high rendering realism with low scene fitting time. Our method efficiently leverages the mult…
Multi-sensor large-scale dataset for multi-view 3D reconstruction
Oleg Voynov, Gleb Bobrovskikh, Pavel Karpyshev +13
We present a new multi-sensor dataset for multi-view 3D surface reconstruction. It includes registered RGB and depth data from sensors of different resolutions and modalities: smar…
DEF: Deep Estimation of Sharp Geometric Features in 3D Shapes
Albert Matveev, Ruslan Rakhimov, Alexey Artemov +6
We propose Deep Estimators of Features (DEFs), a learning-based framework for predicting sharp geometric features in sampled 3D shapes. Differently from existing data-driven method…
Making DensePose fast and light
Ruslan Rakhimov, Emil Bogomolov, Alexandr Notchenko +4
DensePose estimation task is a significant step forward for enhancing user experience computer vision applications ranging from augmented reality to cloth fitting. Existing neural…
Latent Video Transformer
Ruslan Rakhimov, Denis Volkhonskiy, Alexey Artemov +2
The video generation task can be formulated as a prediction of future video frames given some past frames. Recent generative models for videos face the problem of high computationa…