Eleonora Vig

2.9k total citations · 1 hit paper
24 papers, 1.2k citations indexed

About

Eleonora Vig is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Human-Computer Interaction. According to data from OpenAlex, Eleonora Vig has authored 24 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 6 papers in Cognitive Neuroscience and 4 papers in Human-Computer Interaction. Recurrent topics in Eleonora Vig's work include Visual Attention and Saliency Detection (11 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Video Surveillance and Tracking Methods (5 papers). Eleonora Vig is often cited by papers focused on Visual Attention and Saliency Detection (11 papers), Advanced Image and Video Retrieval Techniques (8 papers) and Video Surveillance and Tracking Methods (5 papers). Eleonora Vig collaborates with scholars based in Germany, United States and Australia. Eleonora Vig's co-authors include Adrien Gaidon, Qiao Wang, Yohann Cabon, Michael Dörr, David Cox, Erhardt Barth, Naila Murray, Saumya Jetley, Corentin Henry and Thomas Martinetz and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Vision Research.

In The Last Decade

Eleonora Vig

24 papers receiving 1.2k citations

Hit Papers

VirtualWorlds as Proxy for Multi-object Tracking Analysis 2016 2026 2019 2022 2016 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eleonora Vig Germany 13 984 187 159 149 124 24 1.2k
Menglong Zhu United States 12 1.5k 1.6× 297 1.6× 144 0.9× 298 2.0× 187 1.5× 23 1.9k
Xiangjing An China 14 735 0.7× 139 0.7× 84 0.5× 44 0.3× 72 0.6× 54 946
Hangen He China 17 951 1.0× 194 1.0× 86 0.5× 82 0.6× 74 0.6× 70 1.3k
Wen-Yan Lin Singapore 12 2.0k 2.0× 728 3.9× 83 0.5× 218 1.5× 57 0.5× 22 2.2k
Heinz Hügli Switzerland 15 659 0.7× 250 1.3× 149 0.9× 72 0.5× 105 0.8× 59 856
Simone Frintrop Germany 22 1.5k 1.5× 380 2.0× 324 2.0× 98 0.7× 289 2.3× 62 1.7k
Michael Donoser Austria 16 1000 1.0× 206 1.1× 53 0.3× 127 0.9× 82 0.7× 60 1.3k
Lingxiao Yang China 9 854 0.9× 104 0.6× 81 0.5× 178 1.2× 36 0.3× 23 1.2k

Countries citing papers authored by Eleonora Vig

Since Specialization
Citations

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

Fields of papers citing papers by Eleonora Vig

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eleonora Vig

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

All Works

20 of 20 papers shown
1.
Henry, Corentin, Friedrich Fraundorfer, & Eleonora Vig. (2021). Aerial Road Segmentation in the Presence of Topological Label Noise. elib (German Aerospace Center). 2336–2343. 21 indexed citations
2.
Hou, Yuxin, Eleonora Vig, Michael Donoser, & Loris Bazzani. (2021). Learning Attribute-driven Disentangled Representations for Interactive Fashion Retrieval. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 12127–12137. 36 indexed citations
3.
Azimi, Seyed Majid, Corentin Henry, Lars Sommer, Arne Schumann, & Eleonora Vig. (2019). SkyScapes Fine-Grained Semantic Understanding of Aerial Scenes. elib (German Aerospace Center). 7392–7402. 47 indexed citations
4.
Kurz, Franz, Eleonora Vig, Corentin Henry, et al.. (2018). DLRAD - A first look on the new vision and mapping benchmark dataset. 1 indexed citations
5.
Cerra, Daniele, Miguel Pato, E. Carmona, et al.. (2018). Combining Deep and Shallow Neural Networks with Ad Hoc Detectors for the Classification of Complex Multi-Modal Urban Scenes. elib (German Aerospace Center). 3856–3859. 12 indexed citations
6.
Jetley, Saumya, Naila Murray, & Eleonora Vig. (2016). End-to-End Saliency Mapping via Probability Distribution Prediction. elib (German Aerospace Center). 5753–5761. 85 indexed citations
7.
Marsman, Jan‐Bernard C., Frans W. Cornelissen, Michael Dörr, et al.. (2016). A novel measure to determine viewing priority and its neural correlates in the human brain. Journal of Vision. 16(6). 3–3. 14 indexed citations
8.
Milford, Michael, Walter J. Scheirer, Eleonora Vig, et al.. (2014). Condition-invariant, top-down visual place recognition. 5571–5577. 25 indexed citations
9.
Vig, Eleonora, Michael Dörr, & David Cox. (2014). Large-Scale Optimization of Hierarchical Features for Saliency Prediction in Natural Images. 2798–2805. 263 indexed citations
10.
Milford, Michael, Eleonora Vig, Walter J. Scheirer, & David Cox. (2013). Towards condition-invariant, top-down visual place recognition. QUT ePrints (Queensland University of Technology). 5 indexed citations
11.
Dörr, Michael, Eleonora Vig, & Erhardt Barth. (2013). Efficient image representations and features. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8651. 86510R–86510R. 1 indexed citations
12.
Dörr, Michael, Eleonora Vig, & Erhardt Barth. (2012). Eye movement prediction and variability on natural video data sets. Visual Cognition. 20(4-5). 495–514. 10 indexed citations
13.
Vig, Eleonora, Michael Dörr, & David Cox. (2012). Saliency-based selection of sparse descriptors for action recognition. 1405–1408. 6 indexed citations
14.
Dörr, Michael, Eleonora Vig, & Erhardt Barth. (2012). Colour Saliency on Video. 1 indexed citations
15.
Vig, Eleonora, Michael Dörr, Thomas Martinetz, & Erhardt Barth. (2011). Intrinsic Dimensionality Predicts the Saliency of Natural Dynamic Scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(6). 1080–1091. 33 indexed citations
16.
Vig, Eleonora, Michael Dörr, & Erhardt Barth. (2011). Learned saliency transformations for gaze guidance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7865. 78650W–78650W. 5 indexed citations
17.
Barth, Erhardt, et al.. (2010). Efficient coding and multiple motions. Vision Research. 50(22). 2190–2199. 1 indexed citations
18.
Vig, Eleonora, Michael Dörr, Thomas Martinetz, & Erhardt Barth. (2010). Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes. Cognitive Computation. 3(1). 79–88. 16 indexed citations
19.
Vig, Eleonora, Michael Dörr, & Erhardt Barth. (2009). Efficient visual coding and the predictability of eye movements on natural movies. Spatial Vision. 22(5). 397–408. 28 indexed citations
20.
Dörr, Michael, Eleonora Vig, Karl R. Gegenfurtner, Thomas Martinetz, & Erhardt Barth. (2008). Eye movement modelling and gaze guidance. 6 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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