I am a Research Scientist at VinAI, the first AI research lab in Vietnam with a focus on fundamental research.
My research interests are in computer graphics and computer vision with the focus on 3D deep learning and physically based image synthesis.
Before 2020, I worked as a postdoc with Dr. Toshiya Hachisuka for physically based rendering at the University of Tokyo, with Dr. Sai-Kit Yeung for 3D deep learning at Singapore University of Technology and Design. I completed my PhD at National University of Singapore in 2015, under the supervision of Dr. Kok-Lim Low.
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!
Neural Scene Decoration from a Single Photograph
Self-Supervised Post-Correction for Monte Carlo Denoising
SIGGRAPH North America Conference Proceedings 2022
Regression-based Monte Carlo Integration
SIGGRAPH North America 2022
RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep Learning
International Journal of Computer Vision (IJCV) 2022
SS-3DCapsNet: Self-supervised 3D Capsule Networks for Medical Segmentation on Less Labeled Data
International Symposium on Biomedical Imaging (ISBI) 2022
Single-Click 3D Object Annotation on LiDAR Point Clouds
NeurIPS Data-Centric AI Workshop 2021
Point-set Distances for Learning Representations of 3D Point Clouds
Minimal Adversarial Examples for Deep Learning on 3D Point Clouds
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation
MICCAI 2021 (Oral)
Global Context Aware Convolutions for 3D Point Cloud Understanding
3DV 2020 (Oral)
Deep Combiner for Independent and Correlated Pixel Estimates
SIGGRAPH Asia 2020
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
Pointwise Convolutional Neural Networks
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
A Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation
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: Aug 05, 2022