Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution-Reference-Cited by-同舟云学术

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Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution

Published:2023-10-01 Issue: Volume: Page:12183-12192
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Liu Guandu¹,Ding Yukang²,Li Mading²,Sun Ming²,Wen Xing²,Wang Bin¹

Affiliation:

1. Tsinghua University,School of Software

2. Kuaishou Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10378113.pdf?arnumber=10378113

Reference44 articles.

1. NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study

2. Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network

3. Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile Devices

4. Fast Sparsity-Based Orthogonal Dictionary Learning for Image Restoration

5. Superresolution through neighbor embedding;Chang

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1. Learning kernel parameter lookup tables to implement adaptive bilateral filtering;The Visual Computer;2024-07-01

2. Pest recognition in microstates state: an improvement of YOLOv7 based on Spatial and Channel Reconstruction Convolution for feature redundancy and vision transformer with Bi-Level Routing Attention;Frontiers in Plant Science;2024-02-05

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