Zobrazeno 1 - 10
of 73
pro vyhledávání: '"Jiao, Jichao"'
The soft-argmax operation is widely adopted in neural network-based stereo matching methods to enable differentiable regression of disparity. However, network trained with soft-argmax is prone to being multimodal due to absence of explicit constraint
Externí odkaz:
http://arxiv.org/abs/2410.06527
Autor:
Yang, Zhongyu, Liu, Mai, Xie, Jinluo, Zhang, Yueming, Shen, Chen, Shao, Wei, Jiao, Jichao, Xing, Tengfei, Hu, Runbo, Xu, Pengfei
Autonomous driving without high-definition (HD) maps demands a higher level of active scene understanding. In this competition, the organizers provided the multi-perspective camera images and standard-definition (SD) maps to explore the boundaries of
Externí odkaz:
http://arxiv.org/abs/2406.10125
In recent years, numerous real-time stereo matching methods have been introduced, but they often lack accuracy. These methods attempt to improve accuracy by introducing new modules or integrating traditional methods. However, the improvements are onl
Externí odkaz:
http://arxiv.org/abs/2405.11809
In recent years, due to the wide application of multi-sensor vision systems, multimodal image acquisition technology has continued to develop, and the registration problem based on multimodal images has gradually emerged. Most of the existing multimo
Externí odkaz:
http://arxiv.org/abs/2211.04767
3D shape recognition has attracted more and more attention as a task of 3D vision research. The proliferation of 3D data encourages various deep learning methods based on 3D data. Now there have been many deep learning models based on point-cloud dat
Externí odkaz:
http://arxiv.org/abs/2002.12573
This paper proposes a new framework to solve the problem of monocular visual odometry, called MagicVO . Based on Convolutional Neural Network (CNN) and Bi-directional LSTM (Bi-LSTM), MagicVO outputs a 6-DoF absolute-scale pose at each position of the
Externí odkaz:
http://arxiv.org/abs/1811.10964
Publikováno v:
Multimedia Tools & Applications; Oct2024, Vol. 83 Issue 35, p82035-82047, 13p
Publikováno v:
Machine Learning; Jun2024, Vol. 113 Issue 6, p3829-3848, 20p
Publikováno v:
Multimedia Tools & Applications; Mar2024, Vol. 83 Issue 9, p28027-28038, 12p
Publikováno v:
Multimedia Tools & Applications; Mar2024, Vol. 83 Issue 9, p26255-26279, 25p