H
Himanshu Kumar
Researcher at Indian Institute of Technology, Jodhpur
Publications - 21
Citations - 108
Himanshu Kumar is an academic researcher from Indian Institute of Technology, Jodhpur. The author has contributed to research in topics: Depth map & Point spread function. The author has an hindex of 5, co-authored 19 publications receiving 64 citations. Previous affiliations of Himanshu Kumar include Indian Institute of Technology Kanpur.
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Proceedings ArticleDOI
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report
Andrey Ignatov,Grigory Malivenko,Radu Timofte,Sheng Chen,Xin Xia,Zhaoyan Liu,Yuwei Zhang,Feng Zhu,Jiashi Li,Xuefeng Xiao,Yuan Tian,Xinglong Wu,Christos Kyrkou,Yixin Chen,Zexin Zhang,Yunbo Peng,Yue Lin,Saikat Dutta,Sourya Dipta Das,Nisarg Shah,Himanshu Kumar,Chao Ge,Pei-Lin Wu,Jin-Hua Du,Andrew Batutin,Juan Pablo Federico,Konrad Lyda,Levon Khojoyan,Abhishek Thanki,Sayak Paul,Shahid Siddiqui +30 more
TL;DR: In this article, the first Mobile AI challenge was introduced to develop quantized deep learning-based camera scene classification solutions that can demonstrate a real-time performance on smartphones and IoT platforms.
Proceedings ArticleDOI
Depth estimation from single image using Defocus and Texture cues
TL;DR: A model that combines two monocular depth cues namely Texture and Defocus is presented, which mainly focuses on modifying the erroneous regions in defocus map by using the texture energy present at that region.
Journal ArticleDOI
Depth Map Estimation Using Defocus and Motion Cues
TL;DR: This paper presents a novel framework to generate a more accurate depth map for video using defocus and motion cues and corrects the errors in other parts of depth map caused by inaccurate estimation of defocus blur and motion.
Journal ArticleDOI
Simultaneous Estimation of Defocus and Motion Blurs From Single Image Using Equivalent Gaussian Representation
TL;DR: A novel method to estimate the concurrent defocus and motion blurs in a single image is proposed, which works well for real images as well as for compressed images.
Proceedings ArticleDOI
Hole correction in estimated depth map from single image using color uniformity principle
TL;DR: The proposed method uses color uniformity principle to detect hole regions present in depth map and provides a framework to identify falsely detected holes in order to increase effectiveness of the method.