Pulak Purkait

870 total citations
23 papers, 451 citations indexed

About

Pulak Purkait is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Pulak Purkait has authored 23 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Vision and Pattern Recognition, 6 papers in Aerospace Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Pulak Purkait's work include Advanced Image and Video Retrieval Techniques (8 papers), Advanced Vision and Imaging (7 papers) and Advanced Image Processing Techniques (6 papers). Pulak Purkait is often cited by papers focused on Advanced Image and Video Retrieval Techniques (8 papers), Advanced Vision and Imaging (7 papers) and Advanced Image Processing Techniques (6 papers). Pulak Purkait collaborates with scholars based in India, Australia and United Kingdom. Pulak Purkait's co-authors include Bhabatosh Chanda, Tat-Jun Chin, David Suter, Anders Eriksson, Cheng Zhao, Christopher Zach, Rustam Stolkin, Tom Duckett, Li Sun and Soumitra Samanta and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Sensors.

In The Last Decade

Pulak Purkait

22 papers receiving 432 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Pulak Purkait India 12 360 133 100 99 32 23 451
Jianfeng Zhang China 12 539 1.5× 73 0.5× 104 1.0× 98 1.0× 41 1.3× 50 705
Vassileios Balntas United Kingdom 7 436 1.2× 240 1.8× 44 0.4× 97 1.0× 13 0.4× 10 514
S.A. Nene United States 7 488 1.4× 170 1.3× 99 1.0× 93 0.9× 27 0.8× 7 605
Xinggang Lin China 13 495 1.4× 58 0.4× 55 0.6× 71 0.7× 20 0.6× 79 578
William T. Freeman United States 7 518 1.4× 58 0.4× 57 0.6× 190 1.9× 17 0.5× 8 628
Kwon Junghyun South Korea 9 273 0.8× 101 0.8× 30 0.3× 72 0.7× 8 0.3× 23 366
Ted J. Broida United States 7 604 1.7× 403 3.0× 93 0.9× 136 1.4× 23 0.7× 10 747
Yinlin Hu China 11 354 1.0× 156 1.2× 75 0.8× 49 0.5× 14 0.4× 20 486
Kevin Lin Taiwan 6 599 1.7× 59 0.4× 43 0.4× 121 1.2× 18 0.6× 12 655
Simon Korman Israel 10 384 1.1× 115 0.9× 56 0.6× 47 0.5× 37 1.2× 16 513

Countries citing papers authored by Pulak Purkait

Since Specialization
Citations

This map shows the geographic impact of Pulak Purkait'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 Pulak Purkait with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pulak Purkait more than expected).

Fields of papers citing papers by Pulak Purkait

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pulak Purkait. 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 Pulak Purkait. The network helps show where Pulak Purkait may publish in the future.

Co-authorship network of co-authors of Pulak Purkait

This figure shows the co-authorship network connecting the top 25 collaborators of Pulak Purkait. A scholar is included among the top collaborators of Pulak Purkait 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 Pulak Purkait. Pulak Purkait is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Peixia, Pulak Purkait, Thalaiyasingam Ajanthan, et al.. (2023). Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 1229–1238. 11 indexed citations
2.
Purkait, Pulak, et al.. (2023). Knowledge Combination to Learn Rotated Detection without Rotated Annotation. 15518–15527. 9 indexed citations
3.
Yin, Wei, Thalaiyasingam Ajanthan, Duc-Vu Nguyen, et al.. (2022). Retrieval Augmented Classification for Long-Tail Visual Recognition. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6949–6959. 42 indexed citations
4.
Purkait, Pulak, et al.. (2020). Resolving Marker Pose Ambiguity by Robust Rotation Averaging with Clique Constraints. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 9680–9686. 10 indexed citations
5.
Purkait, Pulak, et al.. (2019). Learning to generate new indoor scenes.. arXiv (Cornell University). 1 indexed citations
6.
Purkait, Pulak, Cheng Zhao, & Christopher Zach. (2018). Synthetic View Generation for Absolute Pose Regression and Image Synthesis.. British Machine Vision Conference. 69. 8 indexed citations
7.
Zhao, Cheng, Li Sun, Pulak Purkait, Tom Duckett, & Rustam Stolkin. (2018). Learning Monocular Visual Odometry with Dense 3D Mapping from Dense 3D Flow. Lincoln Repository (University of Lincoln). 6864–6871. 32 indexed citations
8.
Zhao, Cheng, Li Sun, Pulak Purkait, Tom Duckett, & Rustam Stolkin. (2018). Dense RGB-D Semantic Mapping with Pixel-Voxel Neural Network. Sensors. 18(9). 3099–3099. 20 indexed citations
9.
Purkait, Pulak, Christopher Zach, & Aleš Leonardis. (2017). Rolling Shutter Correction in Manhattan World. University of Birmingham Research Portal (University of Birmingham). 882–890. 25 indexed citations
10.
Chin, Tat-Jun, Pulak Purkait, Anders Eriksson, & David Suter. (2016). Efficient Globally Optimal Consensus Maximisation with Tree Search. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(4). 758–772. 38 indexed citations
11.
Purkait, Pulak, et al.. (2016). Clustering with Hypergraphs: The Case for Large Hyperedges. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(9). 1697–1711. 50 indexed citations
12.
Purkait, Pulak, et al.. (2016). Bishnupur heritage image dataset (BHID). 1–8. 3 indexed citations
13.
Chin, Tat-Jun, Pulak Purkait, Anders Eriksson, & David Suter. (2015). Efficient globally optimal consensus maximisation with tree search. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 37 indexed citations
14.
Purkait, Pulak, Nikhil R. Pal, & Bhabatosh Chanda. (2014). A Fuzzy-Rule-Based Approach for Single Frame Super Resolution. IEEE Transactions on Image Processing. 23(5). 2277–2290. 25 indexed citations
15.
Purkait, Pulak & Bhabatosh Chanda. (2013). A fast and robust deblurring technique on high noise environment. 1. 872–876.
16.
Samanta, Soumitra, Pulak Purkait, & Bhabatosh Chanda. (2012). Indian Classical Dance classification by learning dance pose bases. 265–270. 26 indexed citations
17.
Purkait, Pulak & Bhabatosh Chanda. (2012). Super Resolution Image Reconstruction Through Bregman Iteration Using Morphologic Regularization. IEEE Transactions on Image Processing. 21(9). 4029–4039. 56 indexed citations
18.
Purkait, Pulak & Bhabatosh Chanda. (2012). Digital restoration of damaged mural images. 1–8. 11 indexed citations
19.
Purkait, Pulak & Bhabatosh Chanda. (2011). Morphologic gain-controlled regularization for edge-preserving super-resolution image reconstruction. Signal Image and Video Processing. 7(5). 925–938. 7 indexed citations
20.
Purkait, Pulak, et al.. (2010). A novel technique for sketch to photo synthesis. 219–226. 1 indexed citations

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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