Xiaodi Hou

9.8k total citations · 5 hit papers
11 papers, 6.4k citations indexed

About

Xiaodi Hou is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Xiaodi Hou has authored 11 papers receiving a total of 6.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 4 papers in Cognitive Neuroscience. Recurrent topics in Xiaodi Hou's work include Visual Attention and Saliency Detection (4 papers), Multimodal Machine Learning Applications (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Xiaodi Hou is often cited by papers focused on Visual Attention and Saliency Detection (4 papers), Multimodal Machine Learning Applications (4 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Xiaodi Hou collaborates with scholars based in China, United States and Myanmar. Xiaodi Hou's co-authors include Liqing Zhang, Christof Koch, Jonathan Harel, Zehua Huang, Ding Liu, Ye Yuan, Garrison W. Cottrell, Pengfei Chen, Panqu Wang and Alan Yuille and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and CaltechAUTHORS (California Institute of Technology).

In The Last Decade

Xiaodi Hou

11 papers receiving 6.2k citations

Hit Papers

Saliency Detection: A Spectral Residual Approach 2007 2026 2013 2019 2007 2018 2014 2011 2018 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaodi Hou China 11 5.3k 1.0k 891 802 784 11 6.4k
Jianbing Shen China 52 7.8k 1.5× 545 0.5× 1.2k 1.3× 581 0.7× 866 1.1× 165 9.2k
Wenguan Wang China 56 9.4k 1.8× 672 0.6× 1.1k 1.2× 831 1.0× 1.9k 2.5× 123 11.1k
Xiang Ruan China 23 6.0k 1.1× 1.3k 1.3× 693 0.8× 1.3k 1.6× 466 0.6× 73 6.5k
Ali Borji United States 33 6.4k 1.2× 1.1k 1.0× 806 0.9× 1.6k 2.0× 509 0.6× 78 7.0k
Dingwen Zhang China 49 6.4k 1.2× 545 0.5× 1.5k 1.7× 539 0.7× 1.7k 2.2× 156 8.2k
Xiaohui Shen United States 42 8.7k 1.6× 407 0.4× 1.3k 1.4× 495 0.6× 1.5k 2.0× 99 9.9k
Yun Liu China 34 3.9k 0.7× 235 0.2× 825 0.9× 454 0.6× 737 0.9× 114 5.2k
Niloy J. Mitra United Kingdom 57 9.6k 1.8× 1.0k 1.0× 628 0.7× 785 1.0× 320 0.4× 222 14.2k
Runmin Cong China 38 6.1k 1.1× 310 0.3× 2.2k 2.5× 504 0.6× 339 0.4× 109 6.8k
Yichen Wei China 21 8.0k 1.5× 320 0.3× 1.1k 1.2× 260 0.3× 1.7k 2.2× 36 9.8k

Countries citing papers authored by Xiaodi Hou

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodi Hou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaodi Hou

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

All Works

11 of 11 papers shown
1.
Wang, Panqu, Pengfei Chen, Ye Yuan, et al.. (2018). Understanding Convolution for Semantic Segmentation. 1451–1460. 1366 indexed citations breakdown →
2.
Li, Yanghao, Naiyan Wang, Jianping Shi, Xiaodi Hou, & Jiaying Liu. (2018). Adaptive Batch Normalization for practical domain adaptation. Pattern Recognition. 80. 109–117. 361 indexed citations breakdown →
3.
Li, Yanghao, Naiyan Wang, Jiaying Liu, & Xiaodi Hou. (2017). Demystifying Neural Style Transfer. 2230–2236. 300 indexed citations
4.
Li, Yanghao, Naiyan Wang, Jiaying Liu, & Xiaodi Hou. (2017). Factorized Bilinear Models for Image Recognition. 2098–2106. 66 indexed citations
5.
Li, Yanghao, Naiyan Wang, Jianping Shi, Jiaying Liu, & Xiaodi Hou. (2016). Revisiting Batch Normalization For Practical Domain Adaptation. International Conference on Learning Representations. 23 indexed citations
6.
Li, Yin, Xiaodi Hou, Christof Koch, James M. Rehg, & Alan Yuille. (2014). The Secrets of Salient Object Segmentation. SMARTech Repository (Georgia Institute of Technology). 280–287. 922 indexed citations breakdown →
7.
Hou, Xiaodi, Alan Yuille, & Christof Koch. (2013). Boundary Detection Benchmarking: Beyond F-Measures. 2123–2130. 26 indexed citations
8.
Hou, Xiaodi, Jonathan Harel, & Christof Koch. (2011). Image Signature: Highlighting Sparse Salient Regions. IEEE Transactions on Pattern Analysis and Machine Intelligence. 34(1). 194–201. 604 indexed citations breakdown →
9.
Hou, Xiaodi & Liqing Zhang. (2008). Dynamic visual attention: searching for coding length increments. CaltechAUTHORS (California Institute of Technology). 21. 681–688. 306 indexed citations
10.
Hou, Xiaodi & Liqing Zhang. (2007). Color conceptualization. 265–268. 15 indexed citations
11.
Hou, Xiaodi & Liqing Zhang. (2007). Saliency Detection: A Spectral Residual Approach. 1–8. 2387 indexed citations breakdown →

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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