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of 352
pro vyhledávání: '"Ngan, King Ngi"'
Autor:
Wu, Chenhao, Wu, Qingbo, Wei, Haoran, Chen, Shuai, Wang, Lei, Ngan, King Ngi, Meng, Fanman, Li, Hongliang
Despite demonstrating superior rate-distortion (RD) performance, learning-based image compression (LIC) algorithms have been found to be vulnerable to malicious perturbations in recent studies. However, the adversarial attacks considered in existing
Externí odkaz:
http://arxiv.org/abs/2405.07717
Recent years have witnessed the great success of blind image quality assessment (BIQA) in various task-specific scenarios, which present invariable distortion types and evaluation criteria. However, due to the rigid structure and learning framework,
Externí odkaz:
http://arxiv.org/abs/2209.07126
Publikováno v:
In Signal Processing: Image Communication January 2025 130
Due to the lack of natural scene and haze prior information, it is greatly challenging to completely remove the haze from a single image without distorting its visual content. Fortunately, the real-world haze usually presents non-homogeneous distribu
Externí odkaz:
http://arxiv.org/abs/2104.01888
The attention mechanisms have been employed in Convolutional Neural Network (CNN) to enhance the feature representation. However, existing attention mechanisms only concentrate on refining the features inside each sample and neglect the discriminatio
Externí odkaz:
http://arxiv.org/abs/2103.15099
In video-based dynamic point cloud compression (V-PCC), 3D point clouds are projected onto 2D images for compressing with the existing video codecs. However, the existing video codecs are originally designed for natural visual signals, and it fails t
Externí odkaz:
http://arxiv.org/abs/2103.06549
Publikováno v:
In Displays December 2023 80
In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Specifically, we
Externí odkaz:
http://arxiv.org/abs/1905.02114
Autor:
Wu, Fanzi, Bao, Linchao, Chen, Yajing, Ling, Yonggen, Song, Yibing, Li, Songnan, Ngan, King Ngi, Liu, Wei
We address the problem of recovering the 3D geometry of a human face from a set of facial images in multiple views. While recent studies have shown impressive progress in 3D Morphable Model (3DMM) based facial reconstruction, the settings are mostly
Externí odkaz:
http://arxiv.org/abs/1904.04473
Recently, deep supervised hashing methods have become popular for large-scale image retrieval task. To preserve the semantic similarity notion between examples, they typically utilize the pairwise supervision or the triplet supervised information for
Externí odkaz:
http://arxiv.org/abs/1901.03060