Zobrazeno 1 - 10
of 7 134
pro vyhledávání: '"Cheng, Lei"'
Autor:
Cheng, Lei, Hu, Junpeng, Yan, Haodong, Gladkova, Mariia, Huang, Tianyu, Liu, Yun-Hui, Cremers, Daniel, Li, Haoang
Photometric bundle adjustment (PBA) is widely used in estimating the camera pose and 3D geometry by assuming a Lambertian world. However, the assumption of photometric consistency is often violated since the non-diffuse reflection is common in real-w
Externí odkaz:
http://arxiv.org/abs/2409.11854
This paper aims to explain how a deep neural network (DNN) gradually extracts new knowledge and forgets noisy features through layers in forward propagation. Up to now, although the definition of knowledge encoded by the DNN has not reached a consens
Externí odkaz:
http://arxiv.org/abs/2409.08712
To efficiently express tensor data using the Tucker format, a critical task is to minimize the multilinear rank such that the model would not be over-flexible and lead to overfitting. Due to the lack of rank minimization tools in tensor, existing wor
Externí odkaz:
http://arxiv.org/abs/2409.05139
Autor:
Chen, Panqi, Cheng, Lei
This letter introduces a structured high-rank tensor approach for estimating sub-6G uplink channels in multi-user multiple-input and multiple-output (MU-MIMO) systems. To tackle the difficulty of channel estimation in sub-6G bands with hundreds of su
Externí odkaz:
http://arxiv.org/abs/2409.00723
In the fifth-generation new radio (5G NR) frequency division duplex (FDD) massive multiple-input and multiple-output (MIMO) systems, downlink beamforming relies on the acquisition of downlink channel state information (CSI). Codebook based limited fe
Externí odkaz:
http://arxiv.org/abs/2409.00716
In this letter, we investigate the channel estimation problem for MIMO wireless communication systems with movable antennas (MAs) at both the transmitter (Tx) and receiver (Rx). To achieve high channel estimation accuracy with low pilot training over
Externí odkaz:
http://arxiv.org/abs/2407.18773
Autonomous driving holds great promise in addressing traffic safety concerns by leveraging artificial intelligence and sensor technology. Multi-Object Tracking plays a critical role in ensuring safer and more efficient navigation through complex traf
Externí odkaz:
http://arxiv.org/abs/2407.08049
Cross-view geo-localization confronts significant challenges due to large perspective changes, especially when the ground-view query image has a limited field of view with unknown orientation. To bridge the cross-view domain gap, we for the first tim
Externí odkaz:
http://arxiv.org/abs/2407.06861
Visual place recognition (VPR) remains challenging due to significant viewpoint changes and appearance variations. Mainstream works tackle these challenges by developing various feature aggregation methods to transform deep features into robust and c
Externí odkaz:
http://arxiv.org/abs/2407.06730
Self-supervised pretraining (SSP) has been recognized as a method to enhance prediction accuracy in various downstream tasks. However, its efficacy for DNA sequences remains somewhat constrained. This limitation stems primarily from the fact that mos
Externí odkaz:
http://arxiv.org/abs/2405.08538