Kuldeep Kulkarni

1.1k total citations · 1 hit paper
12 papers, 657 citations indexed

About

Kuldeep Kulkarni is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Artificial Intelligence. According to data from OpenAlex, Kuldeep Kulkarni has authored 12 papers receiving a total of 657 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Computer Vision and Pattern Recognition, 6 papers in Computational Mechanics and 3 papers in Artificial Intelligence. Recurrent topics in Kuldeep Kulkarni's work include Sparse and Compressive Sensing Techniques (5 papers), Multimodal Machine Learning Applications (3 papers) and Image and Signal Denoising Methods (2 papers). Kuldeep Kulkarni is often cited by papers focused on Sparse and Compressive Sensing Techniques (5 papers), Multimodal Machine Learning Applications (3 papers) and Image and Signal Denoising Methods (2 papers). Kuldeep Kulkarni collaborates with scholars based in United States, India and Spain. Kuldeep Kulkarni's co-authors include Pavan Turaga, Suhas Lohit, Amit Ashok, Ronan Kerviche, Jian Wang, Aswin C. Sankaranarayanan, Meysam Madadi, Niloy J. Mitra, Sérgio Escalera and Tripti Shukla and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Arizona State University Library Digital Repository (Arizona State University) and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

In The Last Decade

Kuldeep Kulkarni

11 papers receiving 642 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements

2016 464 citations Kuldeep Kulkarni, Suhas Lohit et al. profile →

Peers

Countries citing papers authored by Kuldeep Kulkarni

Since Specialization

Citations

This map shows the geographic impact of Kuldeep Kulkarni's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kuldeep Kulkarni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kuldeep Kulkarni more than expected).

Fields of papers citing papers by Kuldeep Kulkarni

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kuldeep Kulkarni. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kuldeep Kulkarni. The network helps show where Kuldeep Kulkarni may publish in the future.

Co-authorship network of co-authors of Kuldeep Kulkarni

This figure shows the co-authorship network connecting the top 25 collaborators of Kuldeep Kulkarni. A scholar is included among the top collaborators of Kuldeep Kulkarni based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kuldeep Kulkarni. Kuldeep Kulkarni is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

#	Work	Indexed citations
1	Composing Parts for Expressive Object Generation 2025 ·(unknown), (unknown), Kuldeep Kulkarni, (unknown), Srikrishna Karanam	1
2	GEMS: Scene Expansion using Generative Models of Graphs 2023 ·2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) ·(unknown), (unknown), (unknown), (unknown), Kuldeep Kulkarni, Vishwa Vinay	1
3	Blowing in the Wind: CycleNet for Human Cinemagraphs from Still Images 2023 ·(unknown), Niloy J. Mitra, Kuldeep Kulkarni, Chun-Hao P. Huang, (unknown), Meysam Madadi, Sérgio Escalera, Duygu Ceylan	4
4	Scene Graph Driven Text-Prompt Generation for Image Inpainting 2023 ·Tripti Shukla, (unknown), (unknown), Ankita Shukla, Kuldeep Kulkarni, Pavan Turaga	5
5	User-Guided Variable Rate Learned Image Compression 2022 ·2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) ·(unknown), (unknown), (unknown), (unknown), (unknown), Kuldeep Kulkarni	6
6	Rank-Regularized Measurement Operators for Compressive Imaging 2019 ·Suhas Lohit, (unknown), Kuldeep Kulkarni, Pavan Turaga	0
7	CS-VQA: Visual Question Answering with Compressively Sensed Images 2018 ·(unknown), Kuldeep Kulkarni, (unknown), Suhas Lohit, Suren Jayasuriya, Pavan Turaga	8
8	ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Measurements breakdown → 2016 ·Kuldeep Kulkarni, Suhas Lohit, Pavan Turaga, Ronan Kerviche, Amit Ashok	464
9	Direct inference on compressive measurements using convolutional neural networks 2016 ·Suhas Lohit, Kuldeep Kulkarni, Pavan Turaga	72
10	Reconstruction-Free Action Inference from Compressive Imagers 2015 ·IEEE Transactions on Pattern Analysis and Machine Intelligence ·Kuldeep Kulkarni, Pavan Turaga	58
11	Reconstruction-free inference on compressive measurements 2015 ·Arizona State University Library Digital Repository (Arizona State University) ·Suhas Lohit, Kuldeep Kulkarni, Pavan Turaga, Jian Wang, Aswin C. Sankaranarayanan	29
12	Recurrence textures for human activity recognition from compressive cameras 2012 ·Kuldeep Kulkarni, Pavan Turaga	9

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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