Assistant Professor, Trinity College Dublin
binhson.hua (at) tcd.ie / binhson.hua (at) gmail
My current research interests are in the intersection of computer vision and computer graphics, where I focus on developing deep learning techniques for effective 3D deep learning and realistic image synthesis.
Before joining TCD, I was a Research Scientist at VinAI, the first AI research lab in Vietnam with a focus on fundamental research in 2020-2023. I did my postdoctoral research on physically based rendering with Dr. Toshiya Hachisuka at the University of Tokyo, and on 3D deep learning with Dr. Sai-Kit Yeung at Singapore University of Technology and Design. I received my PhD at National University of Singapore in 2015, working with Dr. Kok-Lim Low.
Aug 04, 2023: A co-authored conference paper on Monte Carlo image denoising accepted to SIGGRAPH Asia 2023.
July 14, 2023: Three papers accepted to ICCV 2023 (Stylized neural radiance fields, 360-degree neural scene decoration, and 3D point cloud instance segmentation).
June 22, 2023: Two papers accepted to IROS 2023.
June 20, 2023: I will serve as Area Chair for CVPR 2024.
June 07, 2023: I was recognized as a CVPR 2023 Outstanding Reviewer.
Mar 01, 2023: One paper accepted to CVPR 2023 (3D point cloud instance segmentation)
Oct 11, 2022: Two papers accepted to WACV 2023 (GAN inversion for 3D point clouds, single-image HDR reconstruction) and a paper accepted to ACCV 2022 (self-supervised point cloud learning with multiple-view rendering).
July 04, 2022: Four papers accepted to ECCV 2022 with the following topics: neural scene decoration, 4D point cloud reconstruction, text-to-image synthesis, and few-shot video classification.
June 17, 2022: A paper about style transfer for architectural photographs accepted to ICCP 2022.
Mar 26, 2022: Two co-author papers about Monte Carlo rendering accepted to SIGGRAPH North America 2022.
Mar 03, 2022: A paper on GAN inversion accepted to CVPR 2022.
Feb 14, 2022: An extended version of RIConv++, a simple rotation invariant convolution for point clouds, accepted to IJCV journal 2022.
Oct 20, 2021: A co-author paper on neural sequence transformation was presented at Pacific Graphics 2021 (Computer Graphics Forum).
Sep 29, 2021: A paper on few-shot learning accepted at NeurIPS 2021.
July 23, 2021: Two papers on 3D point cloud learning accepted at ICCV 2021.
June 12, 2021: Two papers on medical segmentation are accepted at MICCAI 2021.
Jan 13, 2021: A paper on network pruning (that retraining with proper learning rate schedules matters) is accepted at ICLR 2021!
Single-Click 3D Object Annotation on LiDAR Point Clouds
NeurIPS Data-Centric AI Workshop 2021
Global Context Aware Convolutions for 3D Point Cloud Understanding
3DV 2020 (Oral)
LCD: Learned Cross-Domain Descriptors for 2D-3D Matching
AAAI 2020 (Oral)
Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data
ICCV 2019 (Oral)
ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics
ICCV 2019 (Oral)
Rotation Invariant Convolutions for 3D Point Clouds Deep Learning
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds
with Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields
CVPR 2019 (Oral)
Real-time Progressive 3D Semantic Segmentation for Indoor Scene
Light Transport Simulation in the Gradient Domain
SIGGRAPH Asia 2018 Courses
Language-Driven Synthesis of 3D Scenes from Scene Databases
SIGGRAPH Asia 2018
Creating and Understanding 3D Annotated Scene Meshes
IROS 2018 Tutorial
Creating Annotated Scene Meshes for Training and Testing Robot Systems
ICRA 2018 Tutorial
SHREC’18: RGB-D Object-to-CAD Retrieval
Eurographics Workshop on 3D Object Retrieval 2018
SceneNN: A Scene Meshes Dataset with aNNotations
3DV 2016 (Best Paper Honorable Mention)
Calibration of Depth Cameras Using Denoised Depth Images
Intrinsic Image Decomposition Using a Sparse Representation of Reflectance
Adaptive Energy Diffusion for Blind Inverse Halftoning
Last update: Oct 27, 2022