School of Computer Science and Statistics

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Trinity College Dublin
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Dr. Binh-Son Hua

Dr. Binh-Son Hua

Assistant Professor, Computer Science


Biography

Binh-Son Hua is an Assistant Professor of Computer Science at Trinity College Dublin. His research interests are at the intersection of computer graphics, computer vision, and machine learning with a focus on photorealistic 3D modeling and rendering using generative AI. He received his PhD in Computer Science from National University of Singapore in 2015, and spent his postdoctoral research at The University of Tokyo, Japan and Singapore University of Technology and Design. He was recognized with the Best Paper Honorable Mention award at International Conference on 3D Vision 2016, and as an Outstanding Reviewer at CVPR 2023. He has been actively serving as an area chair for CVPR 2024, WACV 2024, ACCV 2022 and as a technical program committee member for SIGGRAPH Asia 2024. His research is funded by Science Foundation Ireland under SFI Frontiers for the Future Programme.

Publications and Further Research Outputs

  • Hua, Binh-Son and Low, Kok-Lim, Interactive motion deblurring using light streaks, 2011 18th IEEE International Conference on Image Processing, 2011, pp1553--1556Conference Paper, 2011
  • Wang, Lei and Hua, Binh-Son and Li, Xueqing, Adaptive energy diffusion for blind inverse halftoning, Advances in Multimedia Information Processing-PCM 2010: 11th Pacific Rim Conference on Multimedia, Shanghai, China, September 21-24, 2010, Proceedings, Part I 11, 2010, pp470--480Conference Paper, 2010
  • Hua, Binh-Son and Ng, Tian-Tsong and Low, Kok-Lim, Reconstruction of Depth and Normals From Interreflections, Image Processing (ICIP), 2013 20th IEEE International Conference on, 2013, pp2557--2561Conference Paper, 2013
  • Shen, Li and Yeo, Chuohao and Hua, Binh-Son, Intrinsic Image Decomposition Using a Sparse Representation of Reflectance, Transactions on Pattern Analysis and Machine Intelligence, 2013Journal Article, 2013
  • Hua, Binh-Son and Sato, Imari and Low, Kok-Lim, Direct and progressive reconstruction of dual photography images, 2013 IEEE International Conference on Image Processing, 2013, pp3157--3161Conference Paper, 2013
  • Pahwa, Ramanpreet Singh and Do, Minh N and Ng, Tian Tsong and Hua, Binh-Son, Calibration of depth cameras using denoised depth images, 2014 IEEE International Conference on Image Processing (ICIP), 2014, pp3459--3463Conference Paper, 2014
  • Guided path tracing using clustered virtual point lights in, SIGGRAPH Asia 2015 Posters, 2015, pp1--1 , [Hua, Binh-Son and Low, Kok-Lim]Book Chapter, 2015
  • Nguyen, Duc Thanh and Hua, Binh-Son and Tran, Khoi and Pham, Quang-Hieu and Yeung, Sai-Kit, A field model for repairing 3d shapes, CVPR, 2016, pp5676--5684Conference Paper, 2016
  • Hua, Binh-Son and Pham, Quang-Hieu and Nguyen, Duc Thanh and Tran, Minh-Khoi and Yu, Lap-Fai and Yeung, Sai-Kit, SceneNN: A Scene Meshes Dataset with aNNotations, International Conference on 3D Vision (3DV), 2016, pp92--101Conference Paper, 2016
  • Nguyen, Duc Thanh and Hua, Binh-Son and Yu, Lap-Fai and Yeung, Sai-Kit, A robust 3d-2d interactive tool for scene segmentation and annotation, TVCG, 2017Journal Article, 2017
  • Hua, Binh-Son and Gruson, Adrien and Nowrouzezahrai, Derek and Hachisuka, Toshiya, Gradient-Domain Photon Density Estimation, Computer Graphics Forum, 2017Journal Article, 2017
  • Hua, Binh-Son and Tran, Minh-Khoi and Yeung, Sai-Kit, Pointwise Convolutional Neural Networks, CVPR, 2018Conference Paper, 2018
  • Pham, Quang-Hieu and Hua, Binh-Son and Nguyen, Thanh and Yeung, Sai-Kit, Real-time progressive 3D semantic segmentation for indoor scenes, Winter Conference on Applications of Computer Vision (WACV), 2019, pp1089--1098Conference Paper, 2019
  • Gruson, Adrien and Hua, Binh-Son and Vibert, Nicolas and Nowrouzezahrai, Derek and Hachisuka, Toshiya, Gradient-domain volumetric photon density estimation, ACM Transactions on Graphics (TOG), 37, (4), 2018, p1--13Journal Article, 2018
  • Ma, Rui and Patil, Akshay Gadi and Fisher, Matthew and Li, Manyi and Pirk, Soren and Hua, Binh-Son and Yeung, Sai-Kit and Tong, Xin and Guibas, Leonidas and Zhang, Hao, Language-driven synthesis of 3D scenes from scene databases, ACM Transactions on Graphics (TOG), 37, (6), 2018, p1--16Journal Article, 2018
  • Pham, Quang-Hieu and Nguyen, Duc Thanh and Hua, Binh-Son and Roig, Gemma and Yeung, Sai-Kit, JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields, CVPR, 2019Conference Paper, 2019
  • Hua, Binh-Son and Gruson, Adrien and Petitjean, Victor and Zwicker, Matthias and Nowrouzezahrai, Derek and Eisemann, Elmar and Hachisuka, Toshiya, A Survey on Gradient-Domain Rendering, Computer Graphics Forum, 38, (2), 2019, p455--472Journal Article, 2019
  • Uy, Mikaela Angelina and Pham, Quang-Hieu and Hua, Binh-Son and Nguyen, Thanh and Yeung, Sai-Kit, Revisiting point cloud classification: A new benchmark dataset and classification model on real-world data, ICCV, 2019, pp1588--1597Conference Paper, 2019
  • Zhang, Zhiyuan and Hua, Binh-Son and Rosen, David W and Yeung, Sai-Kit, Rotation invariant convolutions for 3d point clouds deep learning, 2019 International conference on 3d vision (3DV), 2019, pp204--213Conference Paper, 2019
  • Zhang, Zhiyuan and Hua, Binh-Son and Yeung, Sai-Kit, Shellnet: Efficient point cloud convolutional neural networks using concentric shells statistics, ICCV, 2019, pp1607--1616Conference Paper, 2019
  • Pham, Quang-Hieu and Uy, Mikaela Angelina and Hua, Binh-Son and Nguyen, Duc Thanh and Roig, Gemma and Yeung, Sai-Kit, LCD: Learned Cross-Domain Descriptors for 2D-3D Matching, AAAI Conference on Artificial Intelligence, 2020Conference Paper, 2020
  • Zhang, Zhiyuan and Hua, Binh-Son and Chen, Wei and Tian, Yibin and Yeung, Sai-Kit, Global Context Aware Convolutions for 3D Point Cloud Understanding, International Conference on 3D Vision (3DV) 2020, 2020Conference Paper, 2020
  • Kim, Jaeyeon and Hua, Binh-Son and Nguyen, Duc Thanh and Yeung, Sai-Kit, Minimal Adversarial Examples for Deep Learning on 3D Point Clouds, International Conference on Computer Vision (ICCV), 2021Conference Paper, 2021
  • Back, Jonghee and Hua, Binh-Son and Hachisuka, Toshiya and Moon, Bochang, Deep Combiner for Independent and Correlated Pixel Estimates, SIGGRAPH Asia, 2020Journal Article, 2020
  • Nguyen, Trung and Pham, Quang-Hieu and Le, Tam and Pham, Tung and Ho, Nhat and Hua, Binh-Son, Point-set Distances for Learning Representations of 3D Point Clouds, International Conference on Computer Vision (ICCV), 2021Conference Paper, 2021
  • Le, Duong H and Hua, Binh-Son, Network Pruning That Matters: A Case Study on Retraining Variants, International Conference on Learning Representations (ICLR), 2021Conference Paper, 2021
  • Pang, Hong-Wing and Chen, Yingshu and Hua, Binh-Son and Yeung, Sai-Kit, Neural Scene Decoration from a Single Photograph, ECCV 2022, 2022Conference Paper, 2022
  • Mukherjee, Sabyasachi and Mukherjee, Sayan and Hua, Binh-Son and Umetani, Nobuyuki and Meister, Daniel, Neural Sequence Transformation, Computer Graphics Forum, 2021Journal Article, 2021
  • Ho, Ngoc-Vuong and Nguyen, Tan and Diep, Gia-Han and Le, Ngan and Hua, Binh-Son, Point-unet: A context-aware point-based neural network for volumetric segmentation, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021, pp644--655Conference Paper, 2021
  • Nguyen, Tan and Hua, Binh-Son and Le, Ngan, 3d-ucaps: 3d capsules unet for volumetric image segmentation, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021, pp548--558Conference Paper, 2021
  • Le, Duong Hoang and Nguyen, Khoi Duc and Nguyen, Khoi and Tran, Quoc-Huy and Nguyen, Rang and Hua, Binh-Son, POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples, Neural Information Processing Systems, 2021Conference Paper, 2021
  • Dinh, Tan M and Nguyen, Rang and Hua, Binh-Son, TISE: Bag of Metrics for Text-to-Image Synthesis Evaluation, ECCV 2022, 2022Conference Paper, 2022
  • Dinh, Tan M and Tran, Anh Tuan and Nguyen, Rang and Hua, Binh-Son, HyperInverter: Improving StyleGAN Inversion via Hypernetwork, CVPR 2022, 2022Conference Paper, 2022
  • Nguyen, Trung and Hua, Binh-Son and Nguyen, Duc Thanh and Phung, Dinh, Single-Click 3D Object Annotation on LiDAR Point Clouds, NeurIPS Data Centric AI (DCAI) workshop, 2021Conference Paper, 2021
  • Tran, Minh and Ly, Loi and Hua, Binh-Son and Le, Ngan, SS-3DCapsNet: Self-supervised 3D Capsule Networks for Medical Segmentation on Less Labeled Data, The IEEE International Symposium on Biomedical Imaging (ISBI) 2022, 2022Conference Paper, 2022
  • Zhang, Zhiyuan and Hua, Binh-Son and Yeung, Sai-Kit, RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep Learning, International Journal of Computer Vision (IJCV), 2022Journal Article, 2022
  • Vu, Tuan-Anh and Nguyen, Duc-Thanh and Hua, Binh-Son and Pham, Quang-Hieu and Yeung, Sai-Kit, RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds, ECCV 2022, 2022Conference Paper, 2022
  • Back, Jonghee and Hua, Binh-Son and Hachisuka, Toshiya and Moon, Bochang, Self-Supervised Post-Correction for Monte Carlo Denoising, SIGGRAPH Conference Proceedings, 2022Conference Paper, 2022
  • Nguyen, Khoi D and Tran, Quoc-Huy and Nguyen, Khoi and Hua, Binh-Son and Nguyen, Rang, Inductive and Transductive Few-Shot Video Classification via Appearance and Temporal Alignments, ECCV 2022, 2022Conference Paper, 2022
  • Salaun, Corentin and Gruson, Adrien and Hua, Binh-Son and Hachisuka, Toshiya and Singh, Gurprit, Regression-based Monte Carlo integration, ACM Transactions on Graphics (TOG), 41, (4), 2022, p1--14Journal Article, 2022
  • Chen, Yingshu and Vu, Tuan-Anh and Shum, Ka-Chun and Hua, Binh-Son and Yeung, Sai-Kit, Time-of-Day Neural Style Transfer for Architectural Photographs, ICCP 2022, 2022Conference Paper, 2022
  • Tran, Bach and Hua, Binh-Son and Tran, Anh Tuan and Hoai, Minh, Self-Supervised Learning with Multi-View Rendering for 3D Point Cloud Analysis, ACCV, 2022Conference Paper, 2022
  • Le, Phuoc-Hieu and Le, Quynh and Nguyen, Rang and Hua, Binh-Son, Single-Image HDR Reconstruction by Multi-Exposure Generation, WACV, 2023Conference Paper, 2023
  • Kim, Jaeyeon and Hua, Binh-Son and Nguyen, Duc Thanh and Yeung, Sai-Kit, PointInverter: Point Cloud Reconstruction and Editing via a Generative Model with Shape Priors, WACV, 2023Conference Paper, 2023
  • Ngo, Tuan Duc and Hua, Binh-Son and Nguyen, Khoi, ISBNet: a 3D Point Cloud Instance Segmentation Network with Instance-aware Sampling and Box-aware Dynamic Convolution, CVPR 2023, 2023Conference Paper, 2023
  • Shum, Ka Chun and Pang, Hong-Wing and Hua, Binh-Son and Nguyen, Duc Thanh and Yeung, Sai-Kit, Conditional 360-degree Image Synthesis for Immersive Indoor Scene Decoration, ICCV 2023, 2023Conference Paper, 2023
  • Ngo, Tuan Duc and Hua, Binh-Son and Nguyen, Khoi, GaPro: Box-Supervised 3D Point Cloud Instance Segmentation Using Gaussian Processes as Pseudo Labelers, ICCV 2023, 2023Conference Paper, 2023
  • Shum, Ka Chun and Kim, Jaeyeon and Hua, Binh-Son and Nguyen, Duc Thanh and Yeung, Sai-Kit, Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates, CVPR 2024, 2024Conference Paper, 2024
  • Pang, Hong-Wing and Hua, Binh-Son and Yeung, Sai-Kit, Locally Stylized Neural Radiance Fields, ICCV 2023, 2023Conference Paper, 2023
  • Zheng, Ziqiang and Chen, Yingshu and Hua, Binh-Son and Wu, Yang and Yeung, Sai-Kit, Cross-Domain Autonomous Driving Perception using Contrastive Appearance Adaptation, IROS 2023, 2023Conference Paper, 2023
  • Zheng, Ziqiang and Chen, Yingshu and Hua, Binh-Son and Yeung, Sai-Kit, CompUDA: Compositional Unsupervised Domain Adaptation for Semantic Segmentation under Adverse Conditions, IROS 2023, 2023Conference Paper, 2023
  • Back, Jonghee and Hua, Binh-Son and Hachisuka, Toshiya and Moon, Bochang, Input-Dependent Uncorrelated Weighting for Monte Carlo Denoising, SIGGRAPH Asia Conference, 2023Conference Paper, 2023
  • Vu, Tuan-Anh and Sarkar, Srinjay and Zhang, Zhiyuan and Hua, Binh-Son and Yeung, Sai-Kit, Test-Time Augmentation for 3D Point Cloud Classification and Segmentation, International Conference on 3D Vision (3DV) 2024, 2024Conference Paper, 2024
  • Ziqiang Zheng, Haixin Liang, Binh-Son Hua, Yue Him Wong, Put ANG Jr, Apple Pui Yi CHUI, Sai-Kit Yeung, CoralSCOP: Segment any Coral Image on this Planet, IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR), 2024Conference Paper, 2024

Research Expertise

Computer science - Graphics, visualisation and imaging science, Computer science - Artificial Intelligence,