Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Baráth, Dániel"'
Recovering 3D structure and camera motion from images has been a long-standing focus of computer vision research and is known as Structure-from-Motion (SfM). Solutions to this problem are categorized into incremental and global approaches. Until now,
Externí odkaz:
http://arxiv.org/abs/2407.20219
Autor:
Di Giammarino, Luca, Sun, Boyang, Grisetti, Giorgio, Pollefeys, Marc, Blum, Hermann, Barath, Daniel
Accurate localization in diverse environments is a fundamental challenge in computer vision and robotics. The task involves determining a sensor's precise position and orientation, typically a camera, within a given space. Traditional localization me
Externí odkaz:
http://arxiv.org/abs/2407.15593
This work addresses the challenge of sub-pixel accuracy in detecting 2D local features, a cornerstone problem in computer vision. Despite the advancements brought by neural network-based methods like SuperPoint and ALIKED, these modern approaches lag
Externí odkaz:
http://arxiv.org/abs/2407.11668
We propose a novel visual place recognition approach, VOP, that efficiently addresses occlusions and complex scenes by shifting from traditional reliance on global image similarities and local features to image overlap prediction. The proposed method
Externí odkaz:
http://arxiv.org/abs/2406.16204
Creating 3D semantic reconstructions of environments is fundamental to many applications, especially when related to autonomous agent operation (e.g., goal-oriented navigation or object interaction and manipulation). Commonly, 3D semantic reconstruct
Externí odkaz:
http://arxiv.org/abs/2406.05849
Natural language interfaces to embodied AI are becoming more ubiquitous in our daily lives. This opens further opportunities for language-based interaction with embodied agents, such as a user instructing an agent to execute some task in a specific l
Externí odkaz:
http://arxiv.org/abs/2404.14565
Autor:
Miao, Yang, Engelmann, Francis, Vysotska, Olga, Tombari, Federico, Pollefeys, Marc, Baráth, Dániel Béla
We introduce a novel problem, i.e., the localization of an input image within a multi-modal reference map represented by a database of 3D scene graphs. These graphs comprise multiple modalities, including object-level point clouds, images, attributes
Externí odkaz:
http://arxiv.org/abs/2404.00469
We introduce a novel framework for multiway point cloud mosaicking (named Wednesday), designed to co-align sets of partially overlapping point clouds -- typically obtained from 3D scanners or moving RGB-D cameras -- into a unified coordinate system.
Externí odkaz:
http://arxiv.org/abs/2404.00429
We propose an approach for estimating the relative pose between calibrated image pairs by jointly exploiting points, lines, and their coincidences in a hybrid manner. We investigate all possible configurations where these data modalities can be used
Externí odkaz:
http://arxiv.org/abs/2309.16040
Point cloud registration has seen recent success with several learning-based methods that focus on correspondence matching and, as such, optimize only for this objective. Following the learning step of correspondence matching, they evaluate the estim
Externí odkaz:
http://arxiv.org/abs/2309.16023