4 citations · 6 across the 11 of their papers we have counts for
11 papers
Feature-Guided Diffusion for Non-Differentiable Inverse Rendering
Andrei-Timotei Ardelean, Michael Fischer, Tim Weyrich +1
Inverse rendering is traditionally solved via differentiable renderers and gradient descent, which requires substantial problem-specific engineering and is prone to getting stuck i…
Example-Based Feature Painting on Textures
Andrei-Timotei Ardelean, Tim Weyrich
In this work, we propose a system that covers the complete workflow for achieving controlled authoring and editing of textures that present distinctive local characteristics. These…
Quantized FCA: Efficient Zero-Shot Texture Anomaly Detection
Andrei-Timotei Ardelean, Patrick Rückbeil, Tim Weyrich
Zero-shot anomaly localization is a rising field in computer vision research, with important progress in recent years. This work focuses on the problem of detecting and localizing…
FruitNeRF++: A Generalized Multi-Fruit Counting Method Utilizing Contrastive Learning and Neural Radiance Fields
Lukas Meyer, Andrei-Timotei Ardelean, Tim Weyrich +1
We introduce FruitNeRF++, a novel fruit-counting approach that combines contrastive learning with neural radiance fields to count fruits from unstructured input photographs of orch…
Blind Localization and Clustering of Anomalies in Textures
Andrei-Timotei Ardelean, Tim Weyrich
Anomaly detection and localization in images is a growing field in computer vision. In this area, a seemingly understudied problem is anomaly clustering, i.e., identifying and grou…
High-Fidelity Zero-Shot Texture Anomaly Localization Using Feature Correspondence Analysis
Andrei-Timotei Ardelean, Tim Weyrich
We propose a novel method for Zero-Shot Anomaly Localization on textures. The task refers to identifying abnormal regions in an otherwise homogeneous image. To obtain a high-fideli…
Sphere-Guided Training of Neural Implicit Surfaces
Andreea Dogaru, Andrei Timotei Ardelean, Savva Ignatyev +2
In recent years, neural distance functions trained via volumetric ray marching have been widely adopted for multi-view 3D reconstruction. These methods, however, apply the ray marc…
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…
Stereo Magnification with Multi-Layer Images
Taras Khakhulin, Denis Korzhenkov, Pavel Solovev +3
Representing scenes with multiple semi-transparent colored layers has been a popular and successful choice for real-time novel view synthesis. Existing approaches infer colors and…
Pose Manipulation with Identity Preservation
Andrei-Timotei Ardelean, Lucian Mircea Sasu
This paper describes a new model which generates images in novel poses e.g. by altering face expression and orientation, from just a few instances of a human subject. Unlike previo…