Multi-Distillation Underwater Image Super-Resolution via Wavelet Transform

Autor: Fayaz Ali Dharejo, Basit Alawode, Iyyakutti Iyappan Ganapathi, Le Wang, Ajmal Mian, Radu Timofte, Sajid Javed

Publikováno v: IEEE Access, Vol 12, Pp 131083-131099 (2024)

By improving image quality and resolution, Single Image Super-Resolution (SISR) models help advance understanding of underwater environments. Super-resolution techniques hold promise in addressing these issues by enhancing image details. The transfor

Externí odkaz: https://doaj.org/article/e49753f9bf9d4356a40b5ce874349b12

Outdoor Plant Segmentation With Deep Learning for High-Throughput Field Phenotyping on a Diverse Wheat Dataset

Autor: Radek Zenkl, Radu Timofte, Norbert Kirchgessner, Lukas Roth, Andreas Hund, Luc Van Gool, Achim Walter, Helge Aasen

Publikováno v: Frontiers in Plant Science, Vol 12 (2022)

Robust and automated segmentation of leaves and other backgrounds is a core prerequisite of most approaches in high-throughput field phenotyping. So far, the possibilities of deep learning approaches for this purpose have not been explored adequately

Externí odkaz: https://doaj.org/article/44196e1a9887437c94a170bb7ea74547

PDC-Net+: Enhanced Probabilistic Dense Correspondence Network

Autor: Prune Truong, Martin Danelljan, Radu Timofte, Luc Van Gool

Publikováno v: IEEE Transactions on Pattern Analysis and Machine Intelligence. :1-18

Establishing robust and accurate correspondences between a pair of images is a long-standing computer vision problem with numerous applications. While classically dominated by sparse methods, emerging dense approaches offer a compelling alternative p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1eca68407469af520bd5eeb2a03fe244
https://doi.org/10.1109/tpami.2023.3249225

Audio-Visual Efficient Conformer for Robust Speech Recognition

Autor: Maxime Burchi, Radu Timofte

End-to-end Automatic Speech Recognition (ASR) systems based on neural networks have seen large improvements in recent years. The availability of large scale hand-labeled datasets and sufficient computing resources made it possible to train powerful d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0e18098048b5e0c9fa42ea92259d1a72
http://arxiv.org/abs/2301.01456

MIPI 2022 Challenge on Under-Display Camera Image Restoration: Methods and Results

Autor: Ruicheng Feng, Chongyi Li, Shangchen Zhou, Wenxiu Sun, Qingpeng Zhu, Jun Jiang, Qingyu Yang, Chen Change Loy, Jinwei Gu, Yurui Zhu, Xi Wang, Xueyang Fu, Xiaowei Hu, Jinfan Hu, Xina Liu, Xiangyu Chen, Chao Dong, Dafeng Zhang, Feiyu Huang, Shizhuo Liu, Xiaobing Wang, Zhezhu Jin, Xuhao Jiang, Guangqi Shao, Xiaotao Wang, Lei Lei, Zhao Zhang, Suiyi Zhao, Huan Zheng, Yangcheng Gao, Yanyan Wei, Jiahuan Ren, Tao Huang, Zhenxuan Fang, Mengluan Huang, Junwei Xu, Yong Zhang, Yuechi Yang, Qidi Shu, Zhiwen Yang, Shaocong Li, Mingde Yao, Ruikang Xu, Yuanshen Guan, Jie Huang, Zhiwei Xiong, Hangyan Zhu, Ming Liu, Shaohui Liu, Wangmeng Zuo, Zhuang Jia, Binbin Song, Ziqi Song, Guiting Mao, Ben Hou, Zhimou Liu, Yi Ke, Dengpei Ouyang, Dekui Han, Jinghao Zhang, Qi Zhu, Naishan Zheng, Feng Zhao, Wu Jin, Marcos Conde, Sabari Nathan, Radu Timofte, Tianyi Xu, Jun Xu, P. S. Hrishikesh, Densen Puthussery, C. V. Jiji, Biao Jiang, Yuhan Ding, WanZhang Li, Xiaoyue Feng, Sijing Chen, Tianheng Zhong, Jiyang Lu, Hongming Chen, Zhentao Fan, Xiang Chen

Publikováno v: Lecture Notes in Computer Science ISBN: 9783031250712

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::aa1a936dd43978a65f28dc8b2ddaa88b
https://doi.org/10.1007/978-3-031-25072-9_5