no code implementations • 30 Apr 2024 • Yuekun Dai, Dafeng Zhang, Xiaoming Li, Zongsheng Yue, Chongyi Li, Shangchen Zhou, Ruicheng Feng, Peiqing Yang, Zhezhu Jin, Guanqun Liu, Chen Change Loy, Lize Zhang, Shuai Liu, Chaoyu Feng, Luyang Wang, Shuan Chen, Guangqi Shao, Xiaotao Wang, Lei Lei, Qirui Yang, Qihua Cheng, Zhiqiang Xu, Yihao Liu, Huanjing Yue, Jingyu Yang, Florin-Alexandru Vasluianu, Zongwei Wu, George Ciubotariu, Radu Timofte, Zhao Zhang, Suiyi Zhao, Bo wang, Zhichao Zuo, Yanyan Wei, Kuppa Sai Sri Teja, Jayakar Reddy A, Girish Rongali, Kaushik Mitra, Zhihao Ma, Yongxu Liu, Wanying Zhang, Wei Shang, Yuhong He, Long Peng, Zhongxin Yu, Shaofei Luo, Jian Wang, Yuqi Miao, Baiang Li, Gang Wei, Rakshank Verma, Ritik Maheshwari, Rahul Tekchandani, Praful Hambarde, Satya Narayan Tazi, Santosh Kumar Vipparthi, Subrahmanyam Murala, Haopeng Zhang, Yingli Hou, Mingde Yao, Levin M S, Aniruth Sundararajan, Hari Kumar A
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems.
1 code implementation • CVPR 2023 • Nancy Mehta, Akshay Dudhane, Subrahmanyam Murala, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan
Burst image processing is becoming increasingly popular in recent years.
no code implementations • ICCV 2023 • Prashant W. Patil, Sunil Gupta, Santu Rana, Svetha Venkatesh, Subrahmanyam Murala
Therefore, effective restoration of multi-weather degraded images is an essential prerequisite for successful functioning of such systems.
1 code implementation • CVPR 2023 • Jasdeep Singh, Subrahmanyam Murala, G. Sankara Raju Kosuru
But small motions are prone to noise, illumination changes, large motions, etc.
1 code implementation • 5 Nov 2020 • Gourav Wadhwa, Abhinav Dhall, Subrahmanyam Murala, Usman Tariq
In this paper, we introduce hypergraph convolution on spatial features to learn the complex relationship among the data.
no code implementations • 20 Apr 2019 • Monu Verma, Santosh Kumar Vipparthi, Girdhari Singh, Subrahmanyam Murala
We also propose a Lateral Accretive Hybrid Network (LEARNet) to capture micro-level features of an expression in the facial region.
no code implementations • 7 May 2018 • Sonakshi Mathur, Mallika Chaudhary, Hemant Verma, Murari Mandal, S. K. Vipparthi, Subrahmanyam Murala
A novel color feature descriptor, Multichannel Distributed Local Pattern (MDLP) is proposed in this manuscript.
no code implementations • 19 Apr 2018 • Murari Mandal, Prafulla Saxena, Santosh Kumar Vipparthi, Subrahmanyam Murala
Background subtraction in video provides the preliminary information which is essential for many computer vision applications.
no code implementations • 25 Jan 2018 • Akshay Dudhane, Subrahmanyam Murala
In this paper, a cardinal (red, green and blue) color fusion network for single image haze removal is proposed.
no code implementations • 3 Jan 2018 • Ayan Kumar Bhunia, Avirup Bhattacharyya, Prithaj Banerjee, Partha Pratim Roy, Subrahmanyam Murala
In this paper, we have proposed a novel feature descriptors combining color and texture information collectively.
no code implementations • 7 Sep 2017 • Prithaj Banerjee, Ayan Kumar Bhunia, Avirup Bhattacharyya, Partha Pratim Roy, Subrahmanyam Murala
The proposed method is based on the concept that neighbors of a particular pixel hold a significant amount of texture information that can be considered for efficient texture representation for CBIR.