Eddy Ilg

10.2k total citations · 2 hit papers
17 papers, 4.8k citations indexed

About

Eddy Ilg is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Eddy Ilg has authored 17 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Computer Vision and Pattern Recognition, 3 papers in Computational Mechanics and 3 papers in Aerospace Engineering. Recurrent topics in Eddy Ilg's work include Advanced Vision and Imaging (8 papers), Advanced Neural Network Applications (6 papers) and Video Surveillance and Tracking Methods (3 papers). Eddy Ilg is often cited by papers focused on Advanced Vision and Imaging (8 papers), Advanced Neural Network Applications (6 papers) and Video Surveillance and Tracking Methods (3 papers). Eddy Ilg collaborates with scholars based in Germany, United States and United Kingdom. Eddy Ilg's co-authors include Thomas Brox, Alexey Dosovitskiy, N. Michael Mayer, Tonmoy Saikia, Margret Keuper, Philipp Fischer, Daniel Cremers, Caner Hazırbaş, Patrick van der Smagt and Vladimir Golkov and has published in prestigious journals such as International Journal of Computer Vision, Computer Graphics Forum and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Eddy Ilg

15 papers receiving 4.7k citations

Hit Papers

align trajectories

What are hit papers?

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.

FlowNet: Learning Optical Flow with Convolutional Networks

2015 2.5k citations Alexey Dosovitskiy, Philipp Fischer et al. profile →
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

2017 1.9k citations Eddy Ilg, N. Michael Mayer et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eddy Ilg Germany	10	4.2k	749	684	615	268	17	4.8k
Yuwen Xiong Canada	10	3.9k 0.9×	644 0.9×	886 1.3×	767 1.2×	238 0.9×	17	5.1k
Haozhi Qi United States	9	3.4k 0.8×	608 0.8×	791 1.2×	727 1.2×	241 0.9×	17	4.6k
Guodong Zhang China	8	3.3k 0.8×	543 0.7×	809 1.2×	725 1.2×	225 0.8×	35	4.4k
Steven S. Beauchemin Canada	15	3.5k 0.8×	654 0.9×	311 0.5×	589 1.0×	302 1.1×	45	4.5k
Qifeng Chen Hong Kong	35	4.2k 1.0×	382 0.5×	490 0.7×	930 1.5×	284 1.1×	115	5.2k
Xiaodi Hou China	11	5.3k 1.3×	506 0.7×	784 1.1×	891 1.4×	224 0.8×	11	6.4k
Oncel Tuzel United States	31	3.4k 0.8×	589 0.8×	943 1.4×	897 1.5×	302 1.1×	59	4.5k
Yadong Mu China	26	3.5k 0.8×	301 0.4×	1.3k 2.0×	617 1.0×	331 1.2×	95	4.8k
Gabriel Brostow United Kingdom	27	4.4k 1.1×	900 1.2×	772 1.1×	952 1.5×	135 0.5×	85	5.4k
Koen E. A. van de Sande Netherlands	14	5.2k 1.3×	746 1.0×	1.2k 1.8×	878 1.4×	149 0.6×	19	6.2k

Countries citing papers authored by Eddy Ilg

Since Specialization

Citations

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

Fields of papers citing papers by Eddy Ilg

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eddy Ilg

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

All Works

Sort: Min cites: Since: Top N: Style:

17 of 17 papers shown

1.

Rudnev, Viktor, et al.. (2025). E-3DGS: Event-Based Novel View Rendering of Large-Scale Scenes Using 3D Gaussian Splatting. 926–934.

2.

Lenssen, Jan Eric, Michael Niemeyer, Yiyi Liao, et al.. (2024). Recent Trends in 3D Reconstruction of General Non‐Rigid Scenes. Computer Graphics Forum. 43(2). 12 indexed citations

3.

Ilg, Eddy, et al.. (2024). Neural Parametric Gaussians for Monocular Non-Rigid Object Reconstruction. 10715–10725. 9 indexed citations

4.

Lenssen, Jan Eric, et al.. (2024). Neural Point Cloud Diffusion for Disentangled 3D Shape and Appearance Generation. 8785–8794. 1 indexed citations

5.

Tatarchenko, Maxim, et al.. (2024). Accurate Training Data for Occupancy Map Prediction in Automated Driving Using Evidence Theory. 5281–5290. 2 indexed citations

6.

Ilg, Eddy, et al.. (2023). SimNP: Learning Self-Similarity Priors Between Neural Points. 8807–8818. 5 indexed citations

7.

Ilg, Eddy, et al.. (2022). Recurrent Video Restoration Transformer with Guided Deformable Attention. 378–393.

8.

DeTone, Daniel, Tsun-Yi Yang, Tianwei Shen, et al.. (2022). NinjaDesc: Content-Concealing Visual Descriptors via Adversarial Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 12787–12797. 16 indexed citations

9.

Makansi, Osama, Eddy Ilg, Özgün Çiçek, & Thomas Brox. (2019). Overcoming Limitations of Mixture Density Networks: A Sampling and Fitting Framework for Multimodal Future Prediction. arXiv (Cornell University). 7137–7146. 103 indexed citations

10.

Khoreva, Anna, Rodrigo Benenson, Eddy Ilg, Thomas Brox, & Bernt Schiele. (2019). Lucid Data Dreaming for Video Object Segmentation. International Journal of Computer Vision. 127(9). 1175–1197. 79 indexed citations

11.

Ilg, Eddy, Özgün Çiçek, Aaron Klein, et al.. (2018). Uncertainty Estimates for Optical Flow with Multi-Hypotheses Networks. arXiv (Cornell University). 3 indexed citations

12.

Mayer, N. Michael, Eddy Ilg, Philipp Fischer, et al.. (2018). What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?. International Journal of Computer Vision. 126(9). 942–960. 119 indexed citations

13.

Ilg, Eddy, N. Michael Mayer, Tonmoy Saikia, et al.. (2017). FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. 1647–1655. 1940 indexed citations breakdown →

14.

Khoreva, Anna, Rodrigo Benenson, Eddy Ilg, Thomas Brox, & Bernt Schiele. (2017). Lucid Data Dreaming for Object Tracking. arXiv (Cornell University). 38 indexed citations

15.

Khoreva, Anna, Rodrigo Benenson, Eddy Ilg, Thomas Brox, & Bernt Schiele. (2017). Lucid Data Dreaming for Multiple Object Tracking. arXiv (Cornell University). 15 indexed citations

16.

Dosovitskiy, Alexey, Philipp Fischer, Eddy Ilg, et al.. (2015). FlowNet: Learning Optical Flow with Convolutional Networks. 2758–2766. 2493 indexed citations breakdown →

17.

Ilg, Eddy, et al.. (2014). Reconstruction of rigid body models from motion distorted laser range data using optical flow. 1. 4627–4632. 4 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.

Explore authors with similar magnitude of impact