Yuan, Di Chang, Xiaojun Huang, Po-Yao Liu, Qiao He, Zhenyu
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The training of a feature extraction network typically requires abundant manually annotated training samples, making this a time-consuming and costly process. Accordingly, we propose an effective self-supervised learning-based tracker in a deep correlation framework (named: self-SDCT). Motivated by the forward-backward tracking consistency of a rob...
Wang, Weinong Pei, Wenjie Cao, Qiong Liu, Shu Lu, Guangming Tai, Yu-Wing
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person re-identification aims to identify whether pairs of images belong to the same person or not. This problem is challenging due to large differences in camera views, lighting and background. One of the mainstream in learning CNN features is to design loss functions which reinforce both the class separation and intra-class compactness. In this p...
Ye, Hanrong Liu, Hong Meng, Fanyang Li, Xia
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
RGB-Infrared person re-identification (RGB-IR Re-ID) is a cross-modality matching problem, where the modality discrepancy is a big challenge. Most existing works use Euclidean metric based constraints to resolve the discrepancy between features of images from different modalities. However, these methods are incapable of learning angularly discrimin...
Liu, Zizheng Pan, Xiang Li, Yiming Chen, Zhenzhong
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this article, a new CTU-level bit allocation scheme aimed at subjectively optimized video coding for video conferencing applications is presented, in which the non-cooperative Stackelberg game is used for formulating and solving the bit allocation problem during the encoding process. Videos are divided into the Region of interests (ROI) which at...
Wang, Yingqian Yang, Jungang Wang, Longguang Ying, Xinyi Wu, Tianhao An, Wei Guo, Yulan
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Light field (LF) cameras can record scenes from multiple perspectives, and thus introduce beneficial angular information for image super-resolution (SR). However, it is challenging to incorporate angular information due to disparities among LF images. In this paper, we propose a deformable convolution network (i.e., LF-DFnet) to handle the disparit...
Zhang, Wenhua Jiao, Licheng Li, Yuxuan Liu, Jia
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Many objective tracking methods are based on the framework of correlation filtering (CF) due to its high efficiency. In this paper, we propose a l2 -norm based sparse response regularization term to restrain unexpected crests in response for CF framework. CF trackers learn online to regress the region of interest into a Gaussian response. However, ...
Finlayson, Graham D Zhu, Yuteng
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
When we place a colored filter in front of a camera the effective camera response functions are equal to the given camera spectral sensitivities multiplied by the filter spectral transmittance. In this article, we solve for the filter which returns the modified sensitivities as close to being a linear transformation from the color matching function...
Zhao, Fei Zhang, Ting Song, Yibing Tang, Ming Wang, Xiaobo Wang, Jinqiao
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Siamese networks are prevalent in visual tracking because of the efficient localization. The networks take both a search patch and a target template as inputs where the target template is usually from the initial frame. Meanwhile, Siamese trackers do not update network parameters online for real-time efficiency. The fixed target template and CNN pa...
Di Martino, J Matias Qiu, Qiang Sapiro, Guillermo
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Spoofing attacks are critical threats to modern face recognition systems, and most common countermeasures exploit 2D texture features as they are easy to extract and deploy. 3D shape-based methods can substantially improve spoofing prevention, but extracting the 3D shape of the face often requires complex hardware such as a 3D scanner and expensive...
Wang, Xiao Kihara, Daisuke Luo, Jiebo Qi, Guo-Jun
Published in
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Deep neural networks have been successfully applied to many real-world applications. However, such successes rely heavily on large amounts of labeled data that is expensive to obtain. Recently, many methods for semi-supervised learning have been proposed and achieved excellent performance. In this study, we propose a new EnAET framework to further ...
