Éloi Zablocki

527 total citations
11 papers, 214 citations indexed

About

Éloi Zablocki is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Automotive Engineering. According to data from OpenAlex, Éloi Zablocki has authored 11 papers receiving a total of 214 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 3 papers in Automotive Engineering. Recurrent topics in Éloi Zablocki's work include Advanced Neural Network Applications (4 papers), Autonomous Vehicle Technology and Safety (3 papers) and Advanced Vision and Imaging (2 papers). Éloi Zablocki is often cited by papers focused on Advanced Neural Network Applications (4 papers), Autonomous Vehicle Technology and Safety (3 papers) and Advanced Vision and Imaging (2 papers). Éloi Zablocki collaborates with scholars based in France, Switzerland and Czechia. Éloi Zablocki's co-authors include Patrick Pérez, Matthieu Cord, Hedi Ben-younes, Oriane Siméoni, Gilles Puy, Benjamin Piwowarski, Laure Soulier, Karteek Alahari, Patrick Gallinari and Alexandre Alahi and has published in prestigious journals such as International Journal of Computer Vision, Computer Vision and Image Understanding and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

In The Last Decade

Éloi Zablocki

9 papers receiving 206 citations

Peers

Éloi Zablocki

AI

CVPR

AE

SP

Taylor Mordan Switzerland

Fabian Hüger Germany

Graciela Ramírez-Alonso Mexico

Francesco Solera Italy

Irtiza Hasan Italy

Onay Urfalıoǧlu Germany

Nicholas Rhinehart United States

Stefan Wender Germany

Jacob Walker United States

Blake Wulfe United States

Taylor Mordan Switzerland

Éloi Zablocki

95 ×0.9

AI

142 ×1.5

CVPR

65 ×1.1

AE

12 ×0.8

SP

9 ×0.7

SP

Citations per year, relative to Éloi Zablocki Éloi Zablocki (= 1×) peers Taylor Mordan

Countries citing papers authored by Éloi Zablocki

Since Specialization

Citations

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

Fields of papers citing papers by Éloi Zablocki

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Éloi Zablocki

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

All Works

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11 of 11 papers shown

1.

Zablocki, Éloi, et al.. (2025). Annealed Winner-Takes-All for Motion Forecasting. 1264–1270.

2.

Siméoni, Oriane, Éloi Zablocki, Spyros Gidaris, Gilles Puy, & Patrick Pérez. (2024). Unsupervised Object Localization in the Era of Self-Supervised ViTs: A Survey. International Journal of Computer Vision. 133(2). 781–808. 1 indexed citations

3.

Zablocki, Éloi, et al.. (2024). Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?. SPIRE - Sciences Po Institutional REpository. 18428–18435. 8 indexed citations

4.

Zablocki, Éloi, et al.. (2024). PointBeV: A Sparse Approach to BeV Predictions. SPIRE - Sciences Po Institutional REpository. 15195–15204. 3 indexed citations

5.

Zablocki, Éloi, et al.. (2023). OCTET: Object-aware Counterfactual Explanations. SPIRE - Sciences Po Institutional REpository. 15062–15071. 15 indexed citations

6.

Siméoni, Oriane, et al.. (2023). Unsupervised Object Localization: Observing the Background to Discover Objects. SPIRE - Sciences Po Institutional REpository. 3176–3186. 33 indexed citations

7.

Zablocki, Éloi, et al.. (2022). LiDARTouch: Monocular metric depth estimation with a few-beam LiDAR. Computer Vision and Image Understanding. 227. 103601–103601. 14 indexed citations

8.

Zablocki, Éloi, Hedi Ben-younes, Patrick Pérez, & Matthieu Cord. (2022). Explainability of Deep Vision-Based Autonomous Driving Systems: Review and Challenges. International Journal of Computer Vision. 130(10). 2425–2452. 121 indexed citations

9.

Ben-younes, Hedi, et al.. (2022). Raising context awareness in motion forecasting. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). 8 indexed citations

10.

Zablocki, Éloi, Benjamin Piwowarski, Laure Soulier, & Patrick Gallinari. (2018). Learning Multi-Modal Word Representation Grounded in Visual Context. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 10 indexed citations

11.

Zablocki, Éloi, et al.. (2017). LIP6@CLEF2017: Multi-Modal Spatial Role Labeling using Word Embeddings.. CLEF (Working Notes). 1 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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