B
Bhavya Vasudeva
Researcher at Indian Institute of Technology Roorkee
Publications - 12
Citations - 121
Bhavya Vasudeva is an academic researcher from Indian Institute of Technology Roorkee. The author has contributed to research in topics: Adaptive filter & Compressed sensing. The author has an hindex of 3, co-authored 11 publications receiving 58 citations. Previous affiliations of Bhavya Vasudeva include Indian Statistical Institute.
Papers
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AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov,Radu Timofte,Zhilu Zhang,Ming Liu,Haolin Wang,Wangmeng Zuo,Jiawei Zhang,Ruimao Zhang,Zhanglin Peng,Sijie Ren,Linhui Dai,Xiaohong Liu,Chengqi Li,Jun Chen,Yuichi Ito,Bhavya Vasudeva,Puneesh Deora,Umapada Pal,Zhenyu Guo,Yu Zhu,Tian Liang,Chenghua Li,Cong Leng,Zhihong Pan,Baopu Li,Byung-Hoon Kim,Joonyoung Song,Jong Chul Ye,JaeHyun Baek,Magauiya Zhussip,Yeskendir Koishekenov,Hwechul Cho Ye,Xin Liu,Xueying Hu,Jun Jiang,Jinwei Gu,Kai Li,Pengliang Tan,Bingxin Hou +38 more
TL;DR: This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results, defining the state-of-the-art for practical image signal processing pipeline modeling.
Book ChapterDOI
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
Andrey Ignatov,Radu Timofte,Zhilu Zhang,Ming Liu,Haolin Wang,Wangmeng Zuo,Jiawei Zhang,Ruimao Zhang,Zhanglin Peng,Sijie Ren,Linhui Dai,Xiaohong Liu,Chengqi Li,Jun Chen,Yuichi Ito,Bhavya Vasudeva,Puneesh Deora,Umapada Pal,Zhenyu Guo,Yu Zhu,Tian Liang,Chenghua Li,Cong Leng,Zhihong Pan,Baopu Li,Byung-Hoon Kim,Joonyoung Song,Jong Chul Ye,JaeHyun Baek,Magauiya Zhussip,Yeskendir Koishekenov,Hwechul Cho Ye,Xin Liu,Xueying Hu,Jun Jiang,Jinwei Gu,Kai Li,Pengliang Tan,Bingxin Hou +38 more
TL;DR: The second AIM learned ISP challenge as mentioned in this paper focused on real-world RAW-to-RGB mapping problem, where the goal was to map the original low-quality RAW images captured by the Huawei P20 device to the same photos obtained with the Canon 5D DSLR camera.
Proceedings ArticleDOI
Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial Networks.
TL;DR: In this paper, a generative adversarial network (GAN) based framework for CS-MRI reconstruction is proposed, which combines a combination of patch-based discriminator and structural similarity index based loss.
Posted Content
Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial Networks
TL;DR: A novel generative adversarial network (GAN) based framework for CS-MRI reconstruction is proposed, leveraging a combination of patch-based discriminator and structural similarity index based loss that outperforms state-of-the-art methods in terms of quality of reconstruction and robustness to noise.
Proceedings ArticleDOI
Compressed Sensing MRI Reconstruction with Co-VeGAN: Complex-Valued Generative Adversarial Network
TL;DR: Acomplex-valued generative adversarial network (Co-VeGAN) framework is proposed, which is the first-of-its-kind generative model exploring the use of complex-valued weights and operations and significantly outperforms the existing CS-MRI reconstruction techniques.