Zobrazeno 1 - 10
of 136
pro vyhledávání: '"Woźniak Maciej"'
Autor:
Wozniak, Maciej K., Govindarajan, Hariprasath, Klingner, Marvin, Maurice, Camille, Kiran, B Ravi, Yogamani, Senthil
Recent self-supervised clustering-based pre-training techniques like DINO and Cribo have shown impressive results for downstream detection and segmentation tasks. However, real-world applications such as autonomous driving face challenges with imbala
Externí odkaz:
http://arxiv.org/abs/2410.23085
Autor:
Matejun Marek, Woźniak Maciej
Publikováno v:
Journal of Economics and Management, Vol 41, Iss 3, Pp 5-24 (2020)
Aim/purpose – The aim of the paper is to identify and assess the strategic factors that determine the absorption process of support instruments by SMEs sector companies.
Externí odkaz:
https://doaj.org/article/d49dcca52c8b4f09b7edc7d3972ef14d
In this study, we address a gap in existing unsupervised domain adaptation approaches on LiDAR-based 3D object detection, which have predominantly concentrated on adapting between established, high-density autonomous driving datasets. We focus on spa
Externí odkaz:
http://arxiv.org/abs/2403.17633
Haptic feedback is essential for humans to successfully perform complex and delicate manipulation tasks. A recent rise in tactile sensors has enabled robots to leverage the sense of touch and expand their capability drastically. However, many tasks s
Externí odkaz:
http://arxiv.org/abs/2403.16764
Autor:
Nguyen, Thien-Minh, Yuan, Shenghai, Nguyen, Thien Hoang, Yin, Pengyu, Cao, Haozhi, Xie, Lihua, Wozniak, Maciej, Jensfelt, Patric, Thiel, Marko, Ziegenbein, Justin, Blunder, Noel
Perception plays a crucial role in various robot applications. However, existing well-annotated datasets are biased towards autonomous driving scenarios, while unlabelled SLAM datasets are quickly over-fitted, and often lack environment and domain va
Externí odkaz:
http://arxiv.org/abs/2403.11496
While we can see robots in more areas of our lives, they still make errors. One common cause of failure stems from the robot perception module when detecting objects. Allowing users to correct such errors can help improve the interaction and prevent
Externí odkaz:
http://arxiv.org/abs/2306.14589
Leveraging Trace Theory, we investigate the efficient parallelization of direct solvers for large linear equation systems. Our focus lies on a multi-frontal algorithm, and we present a methodology for achieving near-optimal scheduling on modern massi
Externí odkaz:
http://arxiv.org/abs/2306.08994
Multimodal sensor fusion methods for 3D object detection have been revolutionizing the autonomous driving research field. Nevertheless, most of these methods heavily rely on dense LiDAR data and accurately calibrated sensors which is often not the ca
Externí odkaz:
http://arxiv.org/abs/2306.07344
We present a virtual reality (VR) framework to automate the data collection process in cloth folding tasks. The framework uses skeleton representations to help the user define the folding plans for different classes of garments, allowing for replicat
Externí odkaz:
http://arxiv.org/abs/2305.07493
Publikováno v:
HRI '23: Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction
Many solutions tailored for intuitive visualization or teleoperation of virtual, augmented and mixed (VAM) reality systems are not robust to robot failures, such as the inability to detect and recognize objects in the environment or planning unsafe t
Externí odkaz:
http://arxiv.org/abs/2301.04919