Hwann-Tzong Chen

4.3k total citations · 2 hit papers
57 papers, 2.5k citations indexed

About

Hwann-Tzong Chen is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Hwann-Tzong Chen has authored 57 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Computer Vision and Pattern Recognition, 10 papers in Media Technology and 8 papers in Artificial Intelligence. Recurrent topics in Hwann-Tzong Chen's work include Advanced Vision and Imaging (21 papers), Advanced Image and Video Retrieval Techniques (21 papers) and Advanced Neural Network Applications (9 papers). Hwann-Tzong Chen is often cited by papers focused on Advanced Vision and Imaging (21 papers), Advanced Image and Video Retrieval Techniques (21 papers) and Advanced Neural Network Applications (9 papers). Hwann-Tzong Chen collaborates with scholars based in Taiwan, United States and Japan. Hwann-Tzong Chen's co-authors include Tyng-Luh Liu, Cheng Sun, Min Sun, Shang‐Hong Lai, Min Sun, Cheng Sun, Ding-Jie Chen, Yen‐Yu Lin, Long-Wen Chang and Yi‐Chen Lo 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 Circuits and Systems for Video Technology.

In The Last Decade

Hwann-Tzong Chen

52 papers receiving 2.4k citations

Hit Papers

Direct Voxe... 2005 2026 2012 2019 2022 2005 100 200 300 400 500
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.

  1. Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction
    2022 537 citations Cheng Sun, Min Sun et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →
  2. Local Discriminant Embedding and Its Variants
    2005 447 citations Hwann-Tzong Chen, Tyng-Luh Liu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hwann-Tzong Chen Taiwan 22 2.2k 366 353 326 285 57 2.5k
Miquel Feixas Spain 21 1.2k 0.5× 152 0.4× 487 1.4× 241 0.7× 86 0.3× 77 1.6k
Vibhav Vineet United Kingdom 16 2.0k 0.9× 261 0.7× 70 0.2× 75 0.2× 138 0.5× 45 2.3k
Gianfranco Doretto United States 20 1.9k 0.9× 689 1.9× 191 0.5× 140 0.4× 85 0.3× 63 2.5k
Tyng-Luh Liu Taiwan 22 2.2k 1.0× 509 1.4× 23 0.1× 173 0.5× 384 1.3× 68 2.5k
Brian McWilliams Switzerland 12 1.7k 0.8× 247 0.7× 270 0.8× 109 0.3× 222 0.8× 22 2.0k
Deepu Rajan Singapore 28 2.2k 1.0× 256 0.7× 40 0.1× 60 0.2× 460 1.6× 121 2.8k
Athanassios Skodras Greece 22 2.8k 1.3× 382 1.0× 102 0.3× 145 0.4× 241 0.8× 111 3.5k
Quang-Tuan Luong France 8 1.7k 0.8× 100 0.3× 99 0.3× 67 0.2× 252 0.9× 12 1.9k
Steve Maybank United Kingdom 18 1.2k 0.5× 299 0.8× 47 0.1× 97 0.3× 102 0.4× 31 1.4k
Bruce Walter United States 30 1.8k 0.8× 136 0.4× 1.7k 4.9× 747 2.3× 138 0.5× 75 2.8k

Countries citing papers authored by Hwann-Tzong Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hwann-Tzong Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hwann-Tzong Chen. 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 Hwann-Tzong Chen. The network helps show where Hwann-Tzong Chen may publish in the future.

Co-authorship network of co-authors of Hwann-Tzong Chen

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

All Works

20 of 20 papers shown
1.
Tai, Lin Ai, et al.. (2025). EigenGS Representation: From Eigenspace to Gaussian Image Space. 13487–13496. 1 indexed citations
2.
Ito, Koichi, et al.. (2024). FSErasing: Improving Face Recognition with Data Augmentation Using Face Parsing. IET Biometrics. 2024(1).
3.
Sun, Cheng, Min Sun, & Hwann-Tzong Chen. (2022). Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5449–5459. 537 indexed citations breakdown →
4.
Trigoni, Niki, et al.. (2022). Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstruction. Proceedings of the AAAI Conference on Artificial Intelligence. 36(1). 427–435. 3 indexed citations
5.
Fu, Tsu-Jui, et al.. (2019). Attentive and Adversarial Learning for Video Summarization. 1579–1587. 52 indexed citations
6.
Sun, Cheng, et al.. (2019). HorizonNet: Learning Room Layout With 1D Representation and Pano Stretch Data Augmentation. 1047–1056. 105 indexed citations
7.
Lin, Chieh Hubert, et al.. (2019). COCO-GAN: Generation by Parts via Conditional Coordinating. 4511–4520. 65 indexed citations
8.
Lin, Chieh Hubert, et al.. (2018). COCO-GAN: Conditional Coordinate Generative Adversarial Network. 2 indexed citations
9.
Chen, Ding-Jie, Hwann-Tzong Chen, & Long-Wen Chang. (2018). Interactive 1-bit feedback segmentation using transductive inference. Machine Vision and Applications. 29(4). 617–631. 1 indexed citations
10.
Chen, Hwann-Tzong, et al.. (2018). Self Adversarial Training for Human Pose Estimation. 17–30. 89 indexed citations
11.
Ito, Koichi, Ryuichi Fujimoto, Hwann-Tzong Chen, et al.. (2018). Performance Evaluation of Age Estimation from T1-Weighted Images Using Brain Local Features and CNN. PubMed. 1. 694–697. 7 indexed citations
12.
Chen, Ding-Jie, et al.. (2018). Tap and Shoot Segmentation. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 10 indexed citations
13.
Chen, Ding-Jie, et al.. (2017). Detecting Nonexistent Pedestrians. 182–189. 3 indexed citations
14.
Chen, Hwann-Tzong, et al.. (2012). Learning sparse dictionaries for saliency detection. Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1–5. 3 indexed citations
15.
Liu, Yen‐Cheng & Hwann-Tzong Chen. (2012). Learning to Identify Stable Keypoints. Interdisciplinary Information Sciences. 18(2). 107–112.
16.
Liu, Tyng-Luh, et al.. (2011). Fusing generic objectness and visual saliency for salient object detection. 914–921. 262 indexed citations
17.
Chen, Hwann-Tzong. (2010). Preattentive co-saliency detection. 1117–1120. 58 indexed citations
18.
Chen, Hwann-Tzong, et al.. (2010). A square-root sampling approach to fast histogram-based search. 3043–3049. 10 indexed citations
19.
Liu, Tyng-Luh & Hwann-Tzong Chen. (2002). A variational approach for digital watermarking. 2. 674–677. 1 indexed citations
20.
Liou, Cheng‐Yuan & Hwann-Tzong Chen. (1998). Self-Relaxation for Multilayer Perceptron. 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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