Zobrazeno 1 - 10
of 341
pro vyhledávání: '"CAO Hu"'
Publikováno v:
Youqi dizhi yu caishoulu, Vol 31, Iss 6, Pp 160-167 (2024)
In view of the difficulties in formation energy replenishment and failed injection and production by water drive in low-permeability reservoirs， Shengli Oilfield proposed a water injection technology based on pressure drive for low-permeability res
Externí odkaz:
https://doaj.org/article/32e29033de7244ee9ffeeedec1cc03e4
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
With global warming and enhanced human activities, wetland landscapes are facing environmental problems such as area shrinkage, deterioration of plant and animal living environment, and degradation of ecosystem structure and function. The evolution p
Externí odkaz:
https://doaj.org/article/a0905270d81144488aac2d64c541a2bd
Dataset Distillation is used to create a concise, yet informative, synthetic dataset that can replace the original dataset for training purposes. Some leading methods in this domain prioritize long-range matching, involving the unrolling of training
Externí odkaz:
http://arxiv.org/abs/2407.14245
In frame-based vision, object detection faces substantial performance degradation under challenging conditions due to the limited sensing capability of conventional cameras. Event cameras output sparse and asynchronous events, providing a potential s
Externí odkaz:
http://arxiv.org/abs/2407.12582
Autor:
Song, Rui, Liang, Chenwei, Cao, Hu, Yan, Zhiran, Zimmer, Walter, Gross, Markus, Festag, Andreas, Knoll, Alois
Collaborative perception in automated vehicles leverages the exchange of information between agents, aiming to elevate perception results. Previous camera-based collaborative 3D perception methods typically employ 3D bounding boxes or bird's eye view
Externí odkaz:
http://arxiv.org/abs/2402.07635
Autor:
Hümmer, Christoph, Schwonberg, Manuel, Zhou, Liangwei, Cao, Hu, Knoll, Alois, Gottschalk, Hanno
Domain generalization (DG) remains a significant challenge for perception based on deep neural networks (DNNs), where domain shifts occur due to synthetic data, lighting, weather, or location changes. Vision-language models (VLMs) marked a large step
Externí odkaz:
http://arxiv.org/abs/2312.02021
Point cloud registration is challenging in the presence of heavy outlier correspondences. This paper focuses on addressing the robust correspondence-based registration problem with gravity prior that often arises in practice. The gravity directions a
Externí odkaz:
http://arxiv.org/abs/2311.01432
Autor:
Zhou, Xingcheng, Liu, Mingyu, Yurtsever, Ekim, Zagar, Bare Luka, Zimmer, Walter, Cao, Hu, Knoll, Alois C.
The applications of Vision-Language Models (VLMs) in the field of Autonomous Driving (AD) have attracted widespread attention due to their outstanding performance and the ability to leverage Large Language Models (LLMs). By incorporating language dat
Externí odkaz:
http://arxiv.org/abs/2310.14414
Publikováno v:
IEEE Transactions on Intelligent Vehicles, 2024
Estimating the rigid transformation between two LiDAR scans through putative 3D correspondences is a typical point cloud registration paradigm. Current 3D feature matching approaches commonly lead to numerous outlier correspondences, making outlier-r
Externí odkaz:
http://arxiv.org/abs/2305.11716
In this paper, we present a spatio-temporal tendency reasoning (STR) network for recovering human body pose and shape from videos. Previous approaches have focused on how to extend 3D human datasets and temporal-based learning to promote accuracy and
Externí odkaz:
http://arxiv.org/abs/2210.03659