Titlebook: Computer Vision – ACCV 2020; 15th Asian Conferenc Hiroshi Ishikawa,Cheng-Lin Liu,Jianbo Shi Conference proceedings 2021 Springer Nature Swi

OMIT

0302-9743 , Japan, in November/ December 2020.*.The total of 254 contributions was carefully reviewed and selected from 768 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:..Part I: 3D computer vision; segmentation and grouping..Part II: low-level vision, i

ANTIC

熱烈的歡迎

https://doi.org/10.1007/978-3-319-26047-1iate layers. In this way, GFFRB can enjoy the merits of the lightweight of the group convolution and the high-efficiency of the skip connections, thus achieving better performance compared with most current residual blocks. Experiments on the benchmark test sets show that our models are more efficient than most of the state-of-the-art methods.

myalgia

Accurate and Efficient Single Image Super-Resolution with Matrix Channel Attention NetworkCAB). Several models of different sizes are released to meet various practical requirements. Extensive benchmark experiments show that the proposed models achieve better performance with much fewer multiply-adds and parameters (Source code is at .).

BORE

An Efficient Group Feature Fusion Residual Network for Image Super-Resolutioniate layers. In this way, GFFRB can enjoy the merits of the lightweight of the group convolution and the high-efficiency of the skip connections, thus achieving better performance compared with most current residual blocks. Experiments on the benchmark test sets show that our models are more efficient than most of the state-of-the-art methods.

我的巨大

撤退

Emg827

https://doi.org/10.1007/978-1-349-03555-7ith non-stationary textures remains a challenging task for computer vision. In this paper, a novel approach to image inpainting problem is presented, which adapts exemplar-based methods for deep convolutional neural networks. The concept of . is introduced with the purpose of preserving feature cont

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殘忍