2 citations · 2 across the 6 of their papers we have counts for
8 papers · 1 filter
AgentSTAR: Agentic Shape Tracking and Reconstruction from Monocular Videos
Kirill Mazur, Nikita Karaev, Matthew Chang +2
In this work, we present a method for shape reconstruction and tracking from video via agentic analysis-by-synthesis. Unlike prior methods which first estimate dense pixel correspo…
Triangle Splatting SLAM
Nicholas Fry, Eric Dexheimer, Kirill Mazur +2
We present a dense RGB-D SLAM system using differentiable triangles as the 3D map representation. While 3D Gaussian Splatting has emerged as the leading method for novel-view synth…
KV-Tracker: Real-Time Pose Tracking with Transformers
Marwan Taher, Ignacio Alzugaray, Kirill Mazur +2
Multi-view 3D geometry networks offer a powerful prior but are prohibitively slow for real-time applications. We propose a novel way to adapt them for online use, enabling real-tim…
4D Primitive-Mâché: Glueing Primitives for Persistent 4D Scene Reconstruction
Kirill Mazur, Marwan Taher, Andrew J. Davison
We present a dynamic reconstruction system that receives a casual monocular RGB video as input, and outputs a complete and persistent reconstruction of the scene. In other words, w…
SuperPrimitive: Scene Reconstruction at a Primitive Level
Kirill Mazur, Gwangbin Bae, Andrew J. Davison
Joint camera pose and dense geometry estimation from a set of images or a monocular video remains a challenging problem due to its computational complexity and inherent visual ambi…
Feature-Realistic Neural Fusion for Real-Time, Open Set Scene Understanding
Kirill Mazur, Edgar Sucar, Andrew J. Davison
General scene understanding for robotics requires flexible semantic representation, so that novel objects and structures which may not have been known at training time can be ident…
Point-Based Modeling of Human Clothing
Ilya Zakharkin, Kirill Mazur, Artur Grigorev +1
We propose a new approach to human clothing modeling based on point clouds. Within this approach, we learn a deep model that can predict point clouds of various outfits, for variou…
Cloud Transformers: A Universal Approach To Point Cloud Processing Tasks
Kirill Mazur, Victor Lempitsky
We present a new versatile building block for deep point cloud processing architectures that is equally suited for diverse tasks. This building block combines the ideas of spatial…