Lam Huynh, Ph.D.

Differentiable Ray Tracing with Gaussians for Unified Radio Propagation Simulation and View Synthesis

Niklas Vaara, Lam Huynh, Pekka Sangi, Miguel Bordallo, Janne Heikkilä

arXiv, 2026

project page arXiv code

Cascaded and Generalizable Neural Radiance Fields for Fast View Synthesis

Phong Nguyen-Ha, Lam Huynh, Esa Rahtu, Jiří Matas, Janne Heikkilä

TPAMI, 2023

Fast Neural Architecture Search for Lightweight Dense Prediction Networks

Lam Huynh, Esa Rahtu, Jiří Matas, Janne Heikkilä

arXiv, 2022

Lightweight Monocular Depth with a Novel Neural Architecture Search Method

Lam Huynh, Phong Nguyen-Ha, Jiří Matas, Esa Rahtu, Janne Heikkilä

WACV, 2022

Monocular Depth Estimation Primed by Salient Point Detection and Normalized Hessian Loss

Lam Huynh, Matteo Pedone, Phong Nguyen-Ha, Jiří Matas, Esa Rahtu, Janne Heikkilä

3DV, 2021 (oral)

StressNAS: Affect State and Stress Detection Using Neural Architecture Search

Lam Huynh, Tri Nguyen, Thu Nguyen, Susanna Pirttikangas, Pekka Siirtola

ACM UbiComp-ISWC Adjunct, 2021

Boosting Monocular Depth Estimation with Lightweight 3D Point Fusion

Lam Huynh, Phong Nguyen-Ha, Jiří Matas, Esa Rahtu, Janne Heikkilä

ICCV, 2021

project page arXiv code

Guiding Monocular Depth Estimation Using Depth-Attention Volume

Lam Huynh, Phong Nguyen-Ha, Jiří Matas, Esa Rahtu, Janne Heikkilä

ECCV, 2020

project page arXiv code

Structure-from-motion using convolutional neural networks

Master thesis, funded by Cubicasa Oy and Business Finland

Published on Jultika, 2018

Supervisors: Prof. Janne Heikkilä, Dr. Markus Ylimäki

This work introduces a deep-learning-based structure-from-motion pipeline for the dense 3D scene reconstruction problem.

3D human pose estimation using deep neural networks

Visiting Researcher, IMD lab NAIST, Japan. July-October 2018.

Working on Human 3D Pose Estimation for Sprint (running) using learning-based approaches. This work is a collaboration with MSc. Yuma Ouchi, MSc. Taisei Watanabe, MSc. Ayaka Matsumoto and, Prof. Takafumi Taketomi.

Camera poses and coordinates for dummies

Documentation, Oulu, March 2019

This document is for everyone who still confuse with the relative camera poses and the relationship betweeen the camera and world coordinate. How to do the transformation from one camera coordinate to the other camera coordinate. There are many ways to do this wrong, therefore we should clearly understand these terms.

University pedagogy training

Documentation, Oulu, 30^th March 2019

Learning diary of the basic of university pedagogy, from which I learned the fundamental of teaching and had lot of interesting discussions. Thanks to Dr. Sonja Lutovac for this amazing course.

The four Rs technique to become a deep learner

Documentation, Oulu, 05^th April 2019

A practical scheme to remember and understand deeply what we have learned.

Spring 2018: Deep learning (Dr. Li Liu, Dr. Jie Chen)
Autumn 2019: Deep learning (Dr. Li Liu, Dr. Jie Chen)
Autumn 2020: Deep learning (Dr. Li Liu)
Autumn 2021: Deep learning (Dr. Li Liu)

Worked as a Teaching Assistant alongside Dr. Zhuo Su ('18–'21), Dr. Mohammad Tavakolian ('20), Dr. Yawen Cui ('20), MSc. Jiehua Zhang ('21), MSc. Huali Xu ('21), and MSc. Wuti Xiong ('21).