José M. Alvarez

12.4k total citations · 4 hit papers
78 papers, 3.9k citations indexed

About

José M. Alvarez is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Automotive Engineering. According to data from OpenAlex, José M. Alvarez has authored 78 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Computer Vision and Pattern Recognition, 22 papers in Artificial Intelligence and 20 papers in Automotive Engineering. Recurrent topics in José M. Alvarez's work include Advanced Neural Network Applications (33 papers), Autonomous Vehicle Technology and Safety (20 papers) and Video Surveillance and Tracking Methods (19 papers). José M. Alvarez is often cited by papers focused on Advanced Neural Network Applications (33 papers), Autonomous Vehicle Technology and Safety (20 papers) and Video Surveillance and Tracking Methods (19 papers). José M. Alvarez collaborates with scholars based in Australia, Spain and United States. José M. Alvarez's co-authors include Luis M. Bergasa, Eduardo Romera, Roberto Arroyo, Antonio M. López, Pavlo Molchanov, Hongxu Yin, Jan Kautz, Arun Mallya, Miaomiao Liu and Jiayu Yang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Vehicular Technology.

In The Last Decade

José M. Alvarez

73 papers receiving 3.8k 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.

ERFNet: Efficient Residual Factorized ConvNet for Real-Time Semantic Segmentation

2017 1.1k citations Eduardo Romera, José M. Alvarez et al. IEEE Transactions on Intelligent Transportation Systems profile →
Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion

2020 284 citations Hongxu Yin, Pavlo Molchanov et al. profile →
See through Gradients: Image Batch Recovery via GradInversion

2021 254 citations Hongxu Yin, Arun Mallya et al. profile →
A-ViT: Adaptive Tokens for Efficient Vision Transformer

2022 165 citations Hongxu Yin, Arash Vahdat et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
José M. Alvarez Australia	28	2.9k	1.2k	684	389	386	78	3.9k
Yassine Ruichek France	27	1.6k 0.6×	436 0.4×	248 0.4×	437 1.1×	174 0.5×	176	2.6k
Roberto Arroyo Spain	18	1.5k 0.5×	447 0.4×	448 0.7×	436 1.1×	136 0.4×	28	2.4k
Arturo de la Escalera Spain	30	2.3k 0.8×	377 0.3×	757 1.1×	998 2.6×	209 0.5×	130	3.6k
Zhaoxiang Zhang China	39	5.1k 1.8×	1.9k 1.7×	168 0.2×	522 1.3×	214 0.6×	230	6.5k
Luis M. Bergasa Spain	38	3.1k 1.1×	700 0.6×	1.3k 1.9×	1.1k 2.7×	239 0.6×	174	5.6k
José María Armingol Spain	30	2.1k 0.7×	353 0.3×	833 1.2×	771 2.0×	181 0.5×	135	3.4k
Dariu M. Gavrila Netherlands	38	6.2k 2.1×	1.5k 1.3×	1.7k 2.4×	940 2.4×	247 0.6×	101	7.7k
Kailun Yang China	30	2.3k 0.8×	431 0.4×	227 0.3×	611 1.6×	187 0.5×	147	3.2k
Hongbin Zha China	33	2.9k 1.0×	685 0.6×	452 0.7×	950 2.4×	259 0.7×	289	3.9k
Alper Yılmaz United States	23	4.7k 1.6×	994 0.9×	275 0.4×	1.2k 3.0×	224 0.6×	130	6.0k

Countries citing papers authored by José M. Alvarez

Since Specialization

Citations

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

Fields of papers citing papers by José M. Alvarez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José M. Alvarez. 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 José M. Alvarez. The network helps show where José M. Alvarez may publish in the future.

Co-authorship network of co-authors of José M. Alvarez

This figure shows the co-authorship network connecting the top 25 collaborators of José M. Alvarez. A scholar is included among the top collaborators of José M. Alvarez 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 José M. Alvarez. José M. Alvarez 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:

20 of 20 papers shown

Wang, Zi, et al.. (2025). Enhancing Autonomous Driving Safety with Collision Scenario Integration. 10116–10123.

Clemons, Jason, et al.. (2023). Augmenting Legacy Networks for Flexible Inference. 1–8. 1 indexed citations

Li, Zhiqi, Zhiding Yu, Wenhai Wang, et al.. (2023). FB-BEV: BEV Representation from Forward-Backward View Transformations. 6896–6905. 48 indexed citations

Yin, Hongxu, Arash Vahdat, José M. Alvarez, et al.. (2022). A-ViT: Adaptive Tokens for Efficient Vision Transformer. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 10799–10808. 165 indexed citations breakdown →

Yin, Hongxu, Arun Mallya, Arash Vahdat, et al.. (2021). See through Gradients: Image Batch Recovery via GradInversion. 16332–16341. 254 indexed citations breakdown →

Yu, Zhiding, et al.. (2021). Image-Level or Object-Level? A Tale of Two Resampling Strategies for Long-Tailed Detection. CaltechAUTHORS (California Institute of Technology). 1463–1472. 5 indexed citations

Idelbayev, Yerlan, et al.. (2021). Optimal Quantization using Scaled Codebook. 12090–12099.

Zhang, Yigong, Jin Xie, José M. Alvarez, et al.. (2021). Capitalizing on RGB-FIR Hybrid Imaging for Road Detection. IEEE Transactions on Intelligent Transportation Systems. 23(8). 13819–13834. 7 indexed citations

Yang, Jiayu, Wei Mao, José M. Alvarez, & Miaomiao Liu. (2020). Cost Volume Pyramid Based Depth Inference for Multi-View Stereo. 4876–4885. 214 indexed citations

10.

Yin, Hongxu, Pavlo Molchanov, José M. Alvarez, et al.. (2020). Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion. 8712–8721. 284 indexed citations breakdown →

11.

Alvarez, José M., et al.. (2020). ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 33. 1298–1310. 21 indexed citations

12.

Chitta, Kashyap, José M. Alvarez, Elmar Haußmann, & Clément Farabet. (2019). Less is More: An Exploration of Data Redundancy with Active Dataset Subsampling.. arXiv (Cornell University). 2 indexed citations

13.

Romera, Eduardo, Luis M. Bergasa, Kailun Yang, José M. Alvarez, & Rafael Barea. (2019). Bridging the Day and Night Domain Gap for Semantic Segmentation. IEEE Conference Proceedings. 2019. 1312–1318. 2 indexed citations

14.

Zhang, Yigong, et al.. (2019). Integrating Dense LiDAR-Camera Road Detection Maps by a Multi-Modal CRF Model. IEEE Transactions on Vehicular Technology. 68(12). 11635–11645. 20 indexed citations

15.

Lu, Tao, et al.. (2018). 3-D LiDAR + Monocular Camera: An Inverse-Depth-Induced Fusion Framework for Urban Road Detection. IEEE Transactions on Intelligent Vehicles. 3(3). 351–360. 56 indexed citations

16.

Zhang, Yigong, et al.. (2018). An Illumination-Invariant Nonparametric Model for Urban Road Detection. IEEE Transactions on Intelligent Vehicles. 4(1). 14–23. 10 indexed citations

17.

Alvarez, José M. & Mathieu Salzmann. (2017). Compression-aware Training of Deep Networks. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 30. 856–867. 37 indexed citations

18.

Alvarez, José M., Theo Gevers, & Antonio M. López. (2010). 3D Scene priors for road detection. UvA-DARE (University of Amsterdam). 57–64. 82 indexed citations

19.

Alvarez, José M., Theo Gevers, & Antonio M. López. (2009). Vision-based road detection using road models. 2073–2076. 29 indexed citations

20.

Serrat, Joan, Ferran Diego, Felipe Lumbreras, & José M. Alvarez. (2007). Alignment of videos recorded from moving vehicles. 512–517. 3 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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