Discovering Distinctive "Semantics" in Super-Resolution Networks

Discovering Distinctive "Semantics" in Super-Resolution Networks

1 August 2021

Jinjin Gu

Yu Qiao

Papers citing "Discovering Distinctive "Semantics" in Super-Resolution Networks"

9 / 9 papers shown

Title
Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision Yuandong Pu Le Zhuo Kaiwen Zhu Liangbin Xie Wenlong Zhang Xiangyu Chen Peng Gao Yu Qiao Chao Dong Yihao Liu MLLM 69 1 0 07 Apr 2025
Interpreting Low-level Vision Models with Causal Effect Maps Jinfan Hu Jinjin Gu Shiyao Yu Fanghua Yu Zheyuan Li Zhiyuan You Chaochao Lu Chao Dong CML 50 2 0 29 Jul 2024
CasSR: Activating Image Power for Real-World Image Super-Resolution Haolan Chen Jinhua Hao Kai Zhao Kun Yuan Ming Sun Chao Zhou Wei Hu 34 5 0 18 Mar 2024
A Survey on Neural Network Interpretability Yu Zhang Peter Tiño A. Leonardis K. Tang FaML XAI 144 661 0 28 Dec 2020
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 306 10,368 0 12 Dec 2018
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network Wenzhe Shi Jose Caballero Ferenc Huszár J. Totz Andrew P. Aitken Rob Bishop Daniel Rueckert Zehan Wang SupR 201 5,176 0 16 Sep 2016
DehazeNet: An End-to-End System for Single Image Haze Removal Bolun Cai Xiangmin Xu Kui Jia Chunmei Qing Dacheng Tao 117 2,401 0 28 Jan 2016
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation Vijay Badrinarayanan Alex Kendall R. Cipolla SSeg 446 15,645 0 02 Nov 2015