Zobrazeno 1 - 10
of 213
pro vyhledávání: '"Lu, Yuhang"'
Autor:
Yan, Ziyang, Dong, Wenzhen, Shao, Yihua, Lu, Yuhang, Haiyang, Liu, Liu, Jingwen, Wang, Haozhe, Wang, Zhe, Wang, Yan, Remondino, Fabio, Ma, Yuexin
End-to-end autonomous driving with vision-only is not only more cost-effective compared to LiDAR-vision fusion but also more reliable than traditional methods. To achieve a economical and robust purely visual autonomous driving system, we propose Ren
Externí odkaz:
http://arxiv.org/abs/2409.11356
Large Vision-Language Models (LVLMs) have recently garnered significant attention, with many efforts aimed at harnessing their general knowledge to enhance the interpretability and robustness of autonomous driving models. However, LVLMs typically rel
Externí odkaz:
http://arxiv.org/abs/2409.02914
Over recent years, deep convolutional neural networks have significantly advanced the field of face recognition techniques for both verification and identification purposes. Despite the impressive accuracy, these neural networks are often criticized
Externí odkaz:
http://arxiv.org/abs/2407.05983
Recent years have witnessed significant advancement in face recognition (FR) techniques, with their applications widely spread in people's lives and security-sensitive areas. There is a growing need for reliable interpretations of decisions of such s
Externí odkaz:
http://arxiv.org/abs/2403.04549
Autor:
Lu, Yuhang, Ebrahimi, Touradj
Over the past years, image generation and manipulation have achieved remarkable progress due to the rapid development of generative AI based on deep learning. Recent studies have devoted significant efforts to address the problem of face image manipu
Externí odkaz:
http://arxiv.org/abs/2402.08750
Occupancy prediction has increasingly garnered attention in recent years for its fine-grained understanding of 3D scenes. Traditional approaches typically rely on dense, regular grid representations, which often leads to excessive computational deman
Externí odkaz:
http://arxiv.org/abs/2312.03774
Zero-shot point cloud segmentation aims to make deep models capable of recognizing novel objects in point cloud that are unseen in the training phase. Recent trends favor the pipeline which transfers knowledge from seen classes with labels to unseen
Externí odkaz:
http://arxiv.org/abs/2307.10782
Despite the huge success of deep convolutional neural networks in face recognition (FR) tasks, current methods lack explainability for their predictions because of their "black-box" nature. In recent years, studies have been carried out to give an in
Externí odkaz:
http://arxiv.org/abs/2306.00402
In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite the high accuracy, they are often criticized for lacking explainabilit
Externí odkaz:
http://arxiv.org/abs/2305.08546
Autor:
Lu, Yuhang, Ebrahimi, Touradj
Detecting digital face manipulation in images and video has attracted extensive attention due to the potential risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been employ
Externí odkaz:
http://arxiv.org/abs/2304.06125