Zobrazeno 1 - 10
of 49
pro vyhledávání: '"ZHAO Guoyang"'
Pre-training techniques play a crucial role in deep learning, enhancing models' performance across a variety of tasks. By initially training on large datasets and subsequently fine-tuning on task-specific data, pre-training provides a solid foundatio
Externí odkaz:
http://arxiv.org/abs/2409.20166
Data augmentation is one of the most common tools in deep learning, underpinning many recent advances including tasks such as classification, detection, and semantic segmentation. The standard approach to data augmentation involves simple transformat
Externí odkaz:
http://arxiv.org/abs/2409.20164
Traffic sign is a critical map feature for navigation and traffic control. Nevertheless, current methods for traffic sign recognition rely on traditional deep learning models, which typically suffer from significant performance degradation considerin
Externí odkaz:
http://arxiv.org/abs/2409.15077
Accurate depth estimation is crucial for 3D scene comprehension in robotics and autonomous vehicles. Fisheye cameras, known for their wide field of view, have inherent geometric benefits. However, their use in depth estimation is restricted by a scar
Externí odkaz:
http://arxiv.org/abs/2409.15054
Road lanes are integral components of the visual perception systems in intelligent vehicles, playing a pivotal role in safe navigation. In lane detection tasks, balancing accuracy with real-time performance is essential, yet existing methods often sa
Externí odkaz:
http://arxiv.org/abs/2405.12503
3D lane detection is essential in autonomous driving as it extracts structural and traffic information from the road in three-dimensional space, aiding self-driving cars in logical, safe, and comfortable path planning and motion control. Given the co
Externí odkaz:
http://arxiv.org/abs/2404.06860
Autor:
Liu, Bonan, Zhao, Guoyang, Jiao, Jianhao, Cai, Guang, Li, Chengyang, Yin, Handi, Wang, Yuyang, Liu, Ming, Hui, Pan
Publikováno v:
2024 IEEE International Conference on Robotics and Automation (ICRA)
A Colored point cloud, as a simple and efficient 3D representation, has many advantages in various fields, including robotic navigation and scene reconstruction. This representation is now commonly used in 3D reconstruction tasks relying on cameras a
Externí odkaz:
http://arxiv.org/abs/2404.04693
Curb detection is a crucial function in intelligent driving, essential for determining drivable areas on the road. However, the complexity of road environments makes curb detection challenging. This paper introduces CurbNet, a novel framework for cur
Externí odkaz:
http://arxiv.org/abs/2403.16794
Monocular 3D object detection plays a crucial role in autonomous driving. However, existing monocular 3D detection algorithms depend on 3D labels derived from LiDAR measurements, which are costly to acquire for new datasets and challenging to deploy
Externí odkaz:
http://arxiv.org/abs/2310.00920
The ability to scene understanding in adverse visual conditions, e.g., nighttime, has sparked active research for RGB-Thermal (RGB-T) semantic segmentation. However, it is essentially hampered by two critical problems: 1) the day-night gap of RGB ima
Externí odkaz:
http://arxiv.org/abs/2307.04470