Zobrazeno 1 - 10
of 375
pro vyhledávání: '"Isobe,Takashi"'
Publikováno v:
IEEE Trans. Med. Imaging 42 (2023) 1822
List-mode positron emission tomography (PET) image reconstruction is an important tool for PET scanners with many lines-of-response and additional information such as time-of-flight and depth-of-interaction. Deep learning is one possible solution to
Externí odkaz:
http://arxiv.org/abs/2204.13404
Autor:
Isobe, Takashi, Jia, Xu, Tao, Xin, Li, Changlin, Li, Ruihuang, Shi, Yongjie, Mu, Jing, Lu, Huchuan, Tai, Yu-Wing
Temporal modeling is crucial for video super-resolution. Most of the video super-resolution methods adopt the optical flow or deformable convolution for explicitly motion compensation. However, such temporal modeling techniques increase the model com
Externí odkaz:
http://arxiv.org/abs/2204.07114
Autor:
Hanioka, Nobumitsu, Isobe, Takashi, Saito, Keita, Nagaoka, Kenjiro, Mori, Yoko, Jinno, Hideto, Ohkawara, Susumu, Tanaka-Kagawa, Toshiko
Publikováno v:
In Comparative Biochemistry and Physiology, Part C September 2024 283
In this work, we address the problem of unsupervised domain adaptation for person re-ID where annotations are available for the source domain but not for target. Previous methods typically follow a two-stage optimization pipeline, where the network i
Externí odkaz:
http://arxiv.org/abs/2108.03439
Autor:
Isobe, Takashi, Jia, Xu, Chen, Shuaijun, He, Jianzhong, Shi, Yongjie, Liu, Jianzhuang, Lu, Huchuan, Wang, Shengjin
Recently unsupervised domain adaptation for the semantic segmentation task has become more and more popular due to high-cost of pixel-level annotation on real-world images. However, most domain adaptation methods are only restricted to single-source-
Externí odkaz:
http://arxiv.org/abs/2106.03418
Video super-resolution plays an important role in surveillance video analysis and ultra-high-definition video display, which has drawn much attention in both the research and industrial communities. Although many deep learning-based VSR methods have
Externí odkaz:
http://arxiv.org/abs/2008.05765
Most video super-resolution methods super-resolve a single reference frame with the help of neighboring frames in a temporal sliding window. They are less efficient compared to the recurrent-based methods. In this work, we propose a novel recurrent v
Externí odkaz:
http://arxiv.org/abs/2008.00455
Autor:
Isobe, Takashi, Li, Songjiang, Jia, Xu, Yuan, Shanxin, Slabaugh, Gregory, Xu, Chunjing, Li, Ya-Li, Wang, Shengjin, Tian, Qi
Video super-resolution, which aims at producing a high-resolution video from its corresponding low-resolution version, has recently drawn increasing attention. In this work, we propose a novel method that can effectively incorporate temporal informat
Externí odkaz:
http://arxiv.org/abs/2007.10595
Video-based person re-identification has drawn massive attention in recent years due to its extensive applications in video surveillance. While deep learning-based methods have led to significant progress, these methods are limited by ineffectively u
Externí odkaz:
http://arxiv.org/abs/1905.01722
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