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.
Ensemble of exemplar-SVMs for object detection and beyond
2011567 citationsTomasz Malisiewicz, Abhinav Gupta et al.Figshareprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Tomasz Malisiewicz
Since
Specialization
Citations
This map shows the geographic impact of Tomasz Malisiewicz'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 Tomasz Malisiewicz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tomasz Malisiewicz more than expected).
Fields of papers citing papers by Tomasz Malisiewicz
This network shows the impact of papers produced by Tomasz Malisiewicz. 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 Tomasz Malisiewicz. The network helps show where Tomasz Malisiewicz may publish in the future.
Co-authorship network of co-authors of Tomasz Malisiewicz
This figure shows the co-authorship network connecting the top 25 collaborators of Tomasz Malisiewicz.
A scholar is included among the top collaborators of Tomasz Malisiewicz 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 Tomasz Malisiewicz. Tomasz Malisiewicz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Malisiewicz, Tomasz, Abhinav Shrivastava, Abhinav Gupta, & Alexei A. Efros. (2012). Exemplar-SVMs for visual object detection, label transfer and image retrieval. International Conference on Machine Learning. 7–8.6 indexed citations
10.
Gharbi, Michaël, Tomasz Malisiewicz, Sylvain Paris, & Frédo Durand. (2012). A Gaussian Approximation of Feature Space for Fast Image Similarity. DSpace@MIT (Massachusetts Institute of Technology).19 indexed citations
11.
Malisiewicz, Tomasz, Abhinav Gupta, & Alexei A. Efros. (2011). Ensemble of exemplar-SVMs for object detection and beyond. Figshare. 89–96.567 indexed citations breakdown →
Efros, Alexei A. & Tomasz Malisiewicz. (2011). Exemplar-based representations for object detection, association and beyond. 130–130.8 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.