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.
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
2021202 citationsXavier Giró-i-Nieto et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Xavier Giró-i-Nieto
Since
Specialization
Citations
This map shows the geographic impact of Xavier Giró-i-Nieto'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 Xavier Giró-i-Nieto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xavier Giró-i-Nieto more than expected).
Fields of papers citing papers by Xavier Giró-i-Nieto
This network shows the impact of papers produced by Xavier Giró-i-Nieto. 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 Xavier Giró-i-Nieto. The network helps show where Xavier Giró-i-Nieto may publish in the future.
Co-authorship network of co-authors of Xavier Giró-i-Nieto
This figure shows the co-authorship network connecting the top 25 collaborators of Xavier Giró-i-Nieto.
A scholar is included among the top collaborators of Xavier Giró-i-Nieto 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 Xavier Giró-i-Nieto. Xavier Giró-i-Nieto is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Batard, Thomas, et al.. (2019). Hyperparameter-free losses for model-based monocular reconstruction. QRU Quaderns de Recerca en Urbanisme.1 indexed citations
7.
Bellver, Míriam, et al.. (2019). Budget-aware semi-supervised semantic and instance segmentation. arXiv (Cornell University). 93–102.4 indexed citations
Campos, Víctor, et al.. (2018). Comparing Fixed and Adaptive Computation Time for Recurrent Neural Networks. RECERCAT (Consorci de Serveis Universitaris de Catalunya). 1–8.1 indexed citations
10.
DeBuc, Delia Cabrera, et al.. (2018). Linking media: adopting semantic technologies for multimodal media connection. QRU Quaderns de Recerca en Urbanisme. 1–2.2 indexed citations
McGuinness, Kevin, et al.. (2017). Scan-path Prediction on 360 Degree Images using Saliency Volumes. arXiv (Cornell University).1 indexed citations
14.
Pascual, Santiago, et al.. (2016). Temporal Activity Detection in Untrimmed Videos with Recurrent Neural Networks. RECERCAT (Consorci de Serveis Universitaris de Catalunya). 1–5.14 indexed citations
15.
McGuinness, Kevin, Zhenxing Zhang, Rami Albatal, et al.. (2014). Insight Centre for Data Analytics (DCU) at TRECVid 2014: instance search and semantic indexing tasks. RECERCAT (Consorci de Serveis Universitaris de Catalunya).1 indexed citations
16.
Giró-i-Nieto, Xavier, et al.. (2014). Photo clustering of social events by extending photoTOC to a rich context.4 indexed citations
17.
Giró-i-Nieto, Xavier, et al.. (2014). UPC at MediaEval 2014 Social Event Detection Task. RECERCAT (Consorci de Serveis Universitaris de Catalunya).8 indexed citations
Giró-i-Nieto, Xavier. (2003). La Imatge de la joventut a la premsa escrita. Anàlisi. 105–124.1 indexed citations
20.
Giró-i-Nieto, Xavier. (2003). La imatge de la joventut a la premsa escrita: valors, política i violència. Anàlisi. 105–124.
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.