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.
The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes
2017797 citationsSamuel Rota Bulò, Peter Kontschieder et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Samuel Rota Bulò
Since
Specialization
Citations
This map shows the geographic impact of Samuel Rota Bulò'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 Samuel Rota Bulò with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Rota Bulò more than expected).
Fields of papers citing papers by Samuel Rota Bulò
This network shows the impact of papers produced by Samuel Rota Bulò. 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 Samuel Rota Bulò. The network helps show where Samuel Rota Bulò may publish in the future.
Co-authorship network of co-authors of Samuel Rota Bulò
This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Rota Bulò.
A scholar is included among the top collaborators of Samuel Rota Bulò 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 Samuel Rota Bulò. Samuel Rota Bulò is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Carlucci, Fabio Maria, Lorenzo Porzi, Barbara Caputo, Elisa Ricci, & Samuel Rota Bulò. (2017). AutoDIAL: Automatic Domain Alignment Layers. Institutional Research Information System (Università degli Studi di Trento).176 indexed citations
9.
Bulò, Samuel Rota, Battista Biggio, Ignazio Pillai, Marcello Pelillo, & Fabio Roli. (2016). Randomized Prediction Games for Adversarial Machine Learning. IEEE Transactions on Neural Networks and Learning Systems. 28(11). 2466–2478.40 indexed citations
10.
Sarkar, Advait, Cecily Morrison, Jonas F. Dorn, et al.. (2016). Setwise Comparison. 261–271.16 indexed citations
Kontschieder, Peter, Madalina Fiterau, Antonio Criminisi, & Samuel Rota Bulò. (2015). Deep Neural Decision Forests [Winner of the David Marr Prize 2015].5 indexed citations
Kontschieder, Peter, Samuel Rota Bulò, Antonio Criminisi, et al.. (2012). Context-Sensitive Decision Forests for Object Detection. ARCA (Università Ca' Foscari Venezia). 25. 431–439.22 indexed citations
16.
Kontschieder, Peter, Samuel Rota Bulò, Michael Donoser, Marcello Pelillo, & Horst Bischof. (2012). Evolutionary Hough Games for coherent object detection. Computer Vision and Image Understanding. 116(11). 1149–1158.10 indexed citations
17.
Bulò, Samuel Rota, Peter Kontschieder, Marcello Pelillo, & Horst Bischof. (2012). Structured Local Predictors for image labelling. ARCA (Università Ca' Foscari Venezia). 3530–3537.6 indexed citations
Bulò, Samuel Rota & Marcello Pelillo. (2009). A Game-Theoretic Approach to Hypergraph Clustering. Neural Information Processing Systems. 22. 1571–1579.46 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.