Binh‐Son Hua

2.9k total citations · 2 hit papers
40 papers, 1.5k citations indexed

About

Binh‐Son Hua is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Computer Graphics and Computer-Aided Design. According to data from OpenAlex, Binh‐Son Hua has authored 40 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 15 papers in Computational Mechanics and 13 papers in Computer Graphics and Computer-Aided Design. Recurrent topics in Binh‐Son Hua's work include 3D Shape Modeling and Analysis (15 papers), Computer Graphics and Visualization Techniques (13 papers) and Advanced Vision and Imaging (12 papers). Binh‐Son Hua is often cited by papers focused on 3D Shape Modeling and Analysis (15 papers), Computer Graphics and Visualization Techniques (13 papers) and Advanced Vision and Imaging (12 papers). Binh‐Son Hua collaborates with scholars based in Hong Kong, Vietnam and Singapore. Binh‐Son Hua's co-authors include Sai-Kit Yeung, Minh-Khoi Tran, Zhiyuan Zhang, Quang-Hieu Pham, Duc Thanh Nguyen, Lap-Fai Yu, Rang Nguyen, David W. Rosen, Anh Tran and Toshiya Hachisuka and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Graphics and International Journal of Computer Vision.

In The Last Decade

Binh‐Son Hua

36 papers receiving 1.5k citations

Hit Papers

Pointwise Convolutional Neural Networks 2018 2026 2020 2023 2018 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Binh‐Son Hua Hong Kong 18 836 750 659 388 343 40 1.5k
Bin Fan China 13 680 0.8× 513 0.7× 563 0.9× 324 0.8× 218 0.6× 48 1.2k
Maxim Tatarchenko Germany 6 800 1.0× 673 0.9× 446 0.7× 249 0.6× 382 1.1× 10 1.2k
Gernot Riegler Austria 9 836 1.0× 703 0.9× 547 0.8× 318 0.8× 357 1.0× 12 1.3k
Ali Osman Ulusoy Germany 11 862 1.0× 731 1.0× 616 0.9× 341 0.9× 382 1.1× 13 1.4k
Qiangui Huang United States 7 537 0.6× 437 0.6× 445 0.7× 311 0.8× 150 0.4× 9 949
Wenxuan Wu China 6 823 1.0× 435 0.6× 617 0.9× 435 1.1× 254 0.7× 17 1.2k
Aleksey Golovinskiy United States 15 1.1k 1.4× 1.3k 1.7× 580 0.9× 483 1.2× 653 1.9× 16 2.0k
Matthias NieBner Germany 14 699 0.8× 1.8k 2.3× 562 0.9× 248 0.6× 419 1.2× 17 2.3k
Xian-Feng Han China 13 314 0.4× 536 0.7× 329 0.5× 282 0.7× 105 0.3× 28 1.1k
Yan‐Pei Cao China 17 622 0.7× 576 0.8× 317 0.5× 125 0.3× 422 1.2× 57 1.1k

Countries citing papers authored by Binh‐Son Hua

Since Specialization
Citations

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

Fields of papers citing papers by Binh‐Son Hua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Binh‐Son Hua. 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 Binh‐Son Hua. The network helps show where Binh‐Son Hua may publish in the future.

Co-authorship network of co-authors of Binh‐Son Hua

This figure shows the co-authorship network connecting the top 25 collaborators of Binh‐Son Hua. A scholar is included among the top collaborators of Binh‐Son Hua 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 Binh‐Son Hua. Binh‐Son Hua 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.
Hua, Binh‐Son, et al.. (2025). Advances in 3D Neural Stylization: A Survey. International Journal of Computer Vision. 133(8). 5026–5061.
2.
Nguyen-Ha, Phong, et al.. (2025). SharpDepth: Sharpening Metric Depth Predictions Using Diffusion Distillation. 17060–17069. 1 indexed citations
3.
Hua, Binh‐Son, et al.. (2025). Color Alignment in Diffusion. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 28446–28455.
4.
Tran, Minh–Triet, et al.. (2025). Vision-Aware Text Features in Referring Image Segmentation: From Object Understanding to Context Understanding. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4988–4998.
5.
Kim, Jaeyeon, et al.. (2024). Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 5176–5187. 4 indexed citations
6.
Hua, Binh‐Son, et al.. (2024). CoralSCOP: Segment any COral Image on this Planet. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 28170–28180. 7 indexed citations
7.
Zhang, Zhiyuan, et al.. (2024). Test-Time Augmentation for 3D Point Cloud Classification and Segmentation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1543–1553. 3 indexed citations
8.
Ngo, Tuan, Binh‐Son Hua, & Khoi Nguyen. (2023). ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution. 13550–13559. 32 indexed citations
9.
Hua, Binh‐Son, et al.. (2023). Cross-Domain Autonomous Driving Perception Using Contrastive Appearance Adaptation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 3240–3247.
10.
Hua, Binh‐Son, et al.. (2023). CompUDA: Compositional Unsupervised Domain Adaptation for Semantic Segmentation Under Adverse Conditions. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 7675–7681. 2 indexed citations
11.
Ngo, Tuan, Binh‐Son Hua, & Khoi Nguyen. (2023). GaPro: Box-Supervised 3D Point Cloud Instance Segmentation Using Gaussian Processes as Pseudo Labelers. 17748–17757. 2 indexed citations
12.
Tran, Anh, et al.. (2022). HyperInverter: Improving StyleGAN Inversion via Hypernetwork. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 11379–11388. 76 indexed citations
13.
Hua, Binh‐Son, et al.. (2022). Self-Supervised Post-Correction for Monte Carlo Denoising. 1–8. 9 indexed citations
14.
Tran, Minh C., et al.. (2022). SS-3DCAPSNET: Self-Supervised 3d Capsule Networks for Medical Segmentation on Less Labeled Data. 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI). 1–5. 14 indexed citations
15.
Pham, Quang-Hieu, et al.. (2021). Point-set Distances for Learning Representations of 3D Point Clouds. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 10458–10467. 30 indexed citations
16.
Hua, Binh‐Son, et al.. (2021). Neural Sequence Transformation. Computer Graphics Forum. 40(7). 131–140. 1 indexed citations
17.
Pham, Quang-Hieu, Binh‐Son Hua, Thanh Minh Nguyen, & Sai-Kit Yeung. (2019). Real-Time Progressive 3D Semantic Segmentation for Indoor Scenes. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1089–1098. 53 indexed citations
18.
Ma, Rui, Matthew Fisher, Manyi Li, et al.. (2018). Language-driven synthesis of 3D scenes from scene databases. ACM Transactions on Graphics. 37(6). 1–16. 59 indexed citations
19.
Hua, Binh‐Son, Quang-Hieu Pham, Duc Thanh Nguyen, et al.. (2016). SceneNN: A Scene Meshes Dataset with aNNotations. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 92–101. 186 indexed citations
20.
Li, Shen, Chuohao Yeo, & Binh‐Son Hua. (2013). Intrinsic Image Decomposition Using a Sparse Representation of Reflectance. IEEE Transactions on Pattern Analysis and Machine Intelligence. 35(12). 2904–2915. 37 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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