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.
A large-scale hierarchical multi-view RGB-D object dataset
2011867 citationsKevin Lai, Liefeng Bo et al.profile →
This map shows the geographic impact of Liefeng Bo'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 Liefeng Bo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liefeng Bo more than expected).
This network shows the impact of papers produced by Liefeng Bo. 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 Liefeng Bo. The network helps show where Liefeng Bo may publish in the future.
Co-authorship network of co-authors of Liefeng Bo
This figure shows the co-authorship network connecting the top 25 collaborators of Liefeng Bo.
A scholar is included among the top collaborators of Liefeng Bo 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 Liefeng Bo. Liefeng Bo is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bo, Liefeng, Xiaofeng Ren, & Deborah Fox. (2011). Depth kernel descriptors for object recognition. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.3 indexed citations
15.
Bo, Liefeng & Cristian Sminchisescu. (2009). Efficient Match Kernel between Sets of Features for Visual Recognition. Neural Information Processing Systems. 22. 135–143.136 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.