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.
Long-term recurrent convolutional networks for visual recognition and description
20153.1k citationsJeff Donahue, Lisa Anne Hendricks et al.profile →
Long-Term Recurrent Convolutional Networks for Visual Recognition and Description
20161.1k citationsJeff Donahue, Lisa Anne Hendricks et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
Sequence to Sequence -- Video to Text
2015835 citationsSubhashini Venugopalan, Marcus Rohrbach et al.profile →
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks With Octave Convolution
2019439 citationsYunpeng Chen, Zhicheng Yan et al.profile →
Graph-Based Global Reasoning Networks
2019364 citationsYunpeng Chen, Marcus Rohrbach et al.profile →
Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images
2015323 citationsMateusz Malinowski, Marcus Rohrbach et al.profile →
A database for fine grained activity detection of cooking activities
2012323 citationsMarcus Rohrbach, Saad Amin et al.profile →
FLAVA: A Foundational Language And Vision Alignment Model
2022272 citationsAmanpreet Singh, Ronghang Hu et al.2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)profile →
A dataset for Movie Description
2015245 citationsAnna Rohrbach, Marcus Rohrbach et al.profile →
12-in-1: Multi-Task Vision and Language Representation Learning
2020244 citationsVedanuj Goswami, Marcus Rohrbach et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Marcus Rohrbach
Since
Specialization
Citations
This map shows the geographic impact of Marcus Rohrbach'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 Marcus Rohrbach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcus Rohrbach more than expected).
This network shows the impact of papers produced by Marcus Rohrbach. 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 Marcus Rohrbach. The network helps show where Marcus Rohrbach may publish in the future.
Co-authorship network of co-authors of Marcus Rohrbach
This figure shows the co-authorship network connecting the top 25 collaborators of Marcus Rohrbach.
A scholar is included among the top collaborators of Marcus Rohrbach 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 Marcus Rohrbach. Marcus Rohrbach is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Singh, Amanpreet, Ronghang Hu, Vedanuj Goswami, et al.. (2022). FLAVA: A Foundational Language And Vision Alignment Model. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 15617–15629.272 indexed citations breakdown →
4.
Ebrahimi, Sayna, Mohamed Elhoseiny, Trevor Darrell, & Marcus Rohrbach. (2019). Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract.. Computer Vision and Pattern Recognition. 75–78.2 indexed citations
5.
Chaudhry, Arslan, Marcus Rohrbach, Mohamed Elhoseiny, et al.. (2019). Continual learning with tiny episodic memories. Oxford University Research Archive (ORA) (University of Oxford).100 indexed citations
Donahue, Jeff, Lisa Anne Hendricks, Marcus Rohrbach, et al.. (2016). Long-Term Recurrent Convolutional Networks for Visual Recognition and Description. IEEE Transactions on Pattern Analysis and Machine Intelligence. 39(4). 677–691.1096 indexed citations breakdown →
13.
Malinowski, Mateusz, Marcus Rohrbach, & Mario Fritz. (2015). Ask Your Neurons: A Neural-Based Approach to Answering Questions about Images. 1–9.323 indexed citations breakdown →
14.
Donahue, Jeff, Lisa Anne Hendricks, Sergio Guadarrama, et al.. (2015). Long-term recurrent convolutional networks for visual recognition and description. 2625–2634.3070 indexed citations breakdown →
15.
Rohrbach, Anna, Marcus Rohrbach, Niket Tandon, & Bernt Schiele. (2015). A dataset for Movie Description. 3202–3212.245 indexed citations breakdown →
16.
Rohrbach, Marcus, Sandra Ebert, & Bernt Schiele. (2013). Transfer Learning in a Transductive Setting. Max Planck Digital Library. 26. 46–54.110 indexed citations
Regneri, Michaela, et al.. (2013). Grounding Action Descriptions in Videos. Transactions of the Association for Computational Linguistics. 1. 25–36.260 indexed citations
19.
Rohrbach, Marcus, Saad Amin, Mykhaylo Andriluka, & Bernt Schiele. (2012). A database for fine grained activity detection of cooking activities. 1194–1201.323 indexed citations breakdown →
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.