Imran Saleemi

2.2k total citations · 1 hit paper
14 papers, 1.3k citations indexed

About

Imran Saleemi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Imran Saleemi has authored 14 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 5 papers in Signal Processing. Recurrent topics in Imran Saleemi's work include Human Pose and Action Recognition (7 papers), Video Analysis and Summarization (6 papers) and Anomaly Detection Techniques and Applications (6 papers). Imran Saleemi is often cited by papers focused on Human Pose and Action Recognition (7 papers), Video Analysis and Summarization (6 papers) and Anomaly Detection Techniques and Applications (6 papers). Imran Saleemi collaborates with scholars based in United States. Imran Saleemi's co-authors include Mubarak Shah, Haroon Idrees, Khurram Shafique, Soumyadip Sengupta, Shanchuan Lin, Linjie Yang, Hamid Izadinia, Waqas Sultani, Yang Yang and Jingen Liu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Multimedia.

In The Last Decade

Imran Saleemi

14 papers receiving 1.3k citations

Hit Papers

align trajectories

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.

Multi-source Multi-scale Counting in Extremely Dense Crowd Images

2013 690 citations Haroon Idrees, Imran Saleemi et al. Journal of International Crisis and Risk Communication Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Imran Saleemi United States	12	1.2k	763	169	98	93	14	1.3k
Hefeng Wu China	18	998 0.8×	605 0.8×	118 0.7×	32 0.3×	167 1.8×	54	1.3k
Ramin Mehran United States	6	1.1k 0.9×	1.2k 1.5×	122 0.7×	121 1.2×	61 0.7×	8	1.5k
Mikel Rodríguez United States	11	1.4k 1.2×	837 1.1×	52 0.3×	58 0.6×	33 0.4×	23	1.6k
Stefan Atev United States	12	407 0.3×	174 0.2×	113 0.7×	117 1.2×	45 0.5×	19	668
Fabien Moutarde France	17	503 0.4×	137 0.2×	73 0.4×	47 0.5×	74 0.8×	51	1.0k
Tao Zhao China	9	802 0.7×	353 0.5×	60 0.4×	31 0.3×	16 0.2×	13	916
Wenhan Hu China	3	1.2k 1.0×	452 0.6×	93 0.6×	94 1.0×	11 0.1×	4	1.4k
Dehui Kong China	13	586 0.5×	269 0.4×	43 0.3×	59 0.6×	20 0.2×	91	732
Tianshui Chen China	18	1.4k 1.2×	891 1.2×	22 0.1×	45 0.5×	27 0.3×	59	1.8k
Yong Du China	14	962 0.8×	333 0.4×	39 0.2×	138 1.4×	90 1.0×	40	1.4k

Countries citing papers authored by Imran Saleemi

Since Specialization

Citations

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

Fields of papers citing papers by Imran Saleemi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Imran Saleemi

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

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

Lin, Shanchuan, Linjie Yang, Imran Saleemi, & Soumyadip Sengupta. (2022). Robust High-Resolution Video Matting with Temporal Guidance. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3132–3141. 87 indexed citations

Sultani, Waqas & Imran Saleemi. (2014). Human Action Recognition across Datasets by Foreground-Weighted Histogram Decomposition. Journal of International Crisis and Risk Communication Research. 764–771. 35 indexed citations

Natarajan, Pradeep, Shuang Wu, Florian Luisier, et al.. (2013). BBN VISER TRECVID 2013 Multimedia Event Detection and Multimedia Event Recounting Systems. Journal of International Crisis and Risk Communication Research. 14 indexed citations

Saleemi, Imran & Mubarak Shah. (2013). Multiframe Many–Many Point Correspondence for Vehicle Tracking in High Density Wide Area Aerial Videos. International Journal of Computer Vision. 104(2). 198–219. 67 indexed citations

Idrees, Haroon, et al.. (2013). Multi-source Multi-scale Counting in Extremely Dense Crowd Images. Journal of International Crisis and Risk Communication Research. 2547–2554. 690 indexed citations breakdown →

Saleemi, Imran, et al.. (2013). Multi-agent event recognition by preservation of spatiotemporal relationships between probabilistic models. Image and Vision Computing. 31(9). 603–615. 7 indexed citations

Natarajan, Pradeep, Prem Natarajan, Shuang Wu, et al.. (2012). BBNVISER : BBN VISER TRECVID 2012 Multimedia Event Detection and Multimedia Event Recounting Systems.. TRECVID. 13 indexed citations

Izadinia, Hamid, Imran Saleemi, & Mubarak Shah. (2012). Multimodal Analysis for Identification and Segmentation of Moving-Sounding Objects. IEEE Transactions on Multimedia. 15(2). 378–390. 58 indexed citations

Saleemi, Imran, et al.. (2012). Discovering Motion Primitives for Unsupervised Grouping and One-Shot Learning of Human Actions, Gestures, and Expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(7). 1635–1648. 92 indexed citations

10.

Natarajan, Pradeep, Prem Natarajan, Shuang Wu, et al.. (2011). BBN VISER TRECVID 2011 Multimedia Event Detection System. Journal of International Crisis and Risk Communication Research. 25 indexed citations

11.

Liu, Jingen, Yang Yang, Imran Saleemi, & Mubarak Shah. (2011). Learning semantic features for action recognition via diffusion maps. Computer Vision and Image Understanding. 116(3). 361–377. 39 indexed citations

12.

Saleemi, Imran, et al.. (2011). Similarity invariant classification of events by KL divergence minimization. Journal of International Crisis and Risk Communication Research. 1903–1910. 6 indexed citations

13.

Saleemi, Imran, et al.. (2010). Scene understanding by statistical modeling of motion patterns. Journal of International Crisis and Risk Communication Research. 2069–2076. 95 indexed citations

14.

Saleemi, Imran, Khurram Shafique, & Mubarak Shah. (2009). Probabilistic Modeling of Scene Dynamics for Applications in Visual Surveillance. IEEE Transactions on Pattern Analysis and Machine Intelligence. 31(8). 1472–1485. 98 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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