Zobrazeno 1 - 10
of 2 549
pro vyhledávání: '"A, Baráth"'
Autor:
Xu, Haofei, Peng, Songyou, Wang, Fangjinhua, Blum, Hermann, Barath, Daniel, Geiger, Andreas, Pollefeys, Marc
Gaussian splatting and single/multi-view depth estimation are typically studied in isolation. In this paper, we present DepthSplat to connect Gaussian splatting and depth estimation and study their interactions. More specifically, we first contribute
Externí odkaz:
http://arxiv.org/abs/2410.13862
Reconstructing a 3D scene from unordered images is pivotal in computer vision and robotics, with applications spanning crowd-sourced mapping and beyond. While global Structure-from-Motion (SfM) techniques are scalable and fast, they often compromise
Externí odkaz:
http://arxiv.org/abs/2410.12763
Bistability and snap-through instabilities are central to various mechanisms in nature and engineering, enabling rapid movement and large shape changes with minimal energy input. These phenomena are easily demonstrated by bending a piece of paper int
Externí odkaz:
http://arxiv.org/abs/2410.02402
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
The cornerstone of autonomous vehicles (AV) is a solid perception system, where camera encoders play a crucial role. Existing works usually leverage pre-trained Convolutional Neural Networks (CNN) or Vision Transformers (ViTs) designed for general vi
Externí odkaz:
http://arxiv.org/abs/2407.07276
Visual place recognition methods struggle with occlusions and partial visual overlaps. We propose a novel visual place recognition approach based on overlap prediction, called VOP, shifting from traditional reliance on global image similarities and l
Externí odkaz:
http://arxiv.org/abs/2406.16204
As we push the boundaries of performance in various vision tasks, the models grow in size correspondingly. To keep up with this growth, we need very aggressive pruning techniques for efficient inference and deployment on edge devices. Existing prunin
Externí odkaz:
http://arxiv.org/abs/2406.12079
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