Yancong Lin (林彦聪)

Postdoc, Intelligent Vehicles Group, 3mE, TUDelft.

Working with Prof. Dariu M. Gavrila and Dr. Holger Caesar.

PhD from Pattern Recognition & Bioinformatics, TUDelft (2022).

Worked with Dr.Jan van Gemert and Dr. Silvia-Laura Pintea.


A dedicated, creative, hands-on researcher on machine perception.
Interested in parametric inductive priors and mining corner cases.
Working on data-efficient deep learning for intelligent vehicles.


Email  /  Google Scholar  /  Github  /  LinkedIn

profile
Research

I am enthusiastic about data-efficient learning by pre-wiring deep networks with generic innate priors. My research is about re-parameterizing old-school feature engineering for end2end learning, where the inductive knowledge no longer needs to be learned from big data. I have been working on a variety of tasks on 2D/3D scene parsing. The ultimate goal is to better understand the 3D world without relying on large manually labeled datasets.

News

19/10/2022     I am an outstanding reviewer, ECCV'22!

01/10/2022     Postdoc at the Intelligent Vehicles Group, 3mE, TUDelft.

30/09/2022     Our submission to BMVC'22 on mirror symmetries got accepted!

21/05/2022     I am an outstanding reviewer, CVPR'22!

25/04/2022     I have successfully defended my phd dissertation!

03/03/2022     Our submission to CVPR'22 on vanishing points got accepted!

01/01/2022     New project with an industrial partner: computet vision for aircraft engine inspection.

18/08/2021     Our submission to ICCV'21 workshop (Deep Learning for Geometric Computing): Best student paper award!

23/07/2021     ICCV'21 workshop: 2nd Visual Inductive Priors for Data-Efficient Deep Learning Workshop,

12/07/2021     Congrats to Andrea on defending his master thesis!

26/05/2021     Our submission to ICIP'21 got accepted!

01/10/2020     Congrats to Kang Lang on defending his master thesis!

23/08/2020     ECCV'20 workshop: 1st Visual Inductive Priors for Data-Efficient Deep Learning Workshop,

04/07/2020     Our submission to ECCV'20 on wireframe parsing got accepted!

Publications
Data-efficient learning of geometric structures from single-view images
Yancong Lin
PhD dissertation, 2022
PDF

Key words: geometric priors, wireframes, vanishing points, polygons, planes.

Deep Vanishing Point Detection: Geometric priors make dataset variations vanish
Yancong Lin, Ruben Wiserma, Silvia-Laura Pintea, Klaus Hildebrandt, Elmar Eisemann, Jan van Gemert
CVPR, 2022
arXiv / Code

Hough Transform and Gaussian sphere priors for data-efficient and domain-robust vanishing point detection.

NeRD++: Improved 3D-mirror symmetry learning from a single image
Yancong Lin, Silvia-Laura Pintea, Jan van Gemert
BMVC, 2022
arXiv / Code

Detecting 3D mirror plane from a single image, using feature correlations, mirroring, multi-scale spherical convs.

Investigating transformers in the decomposition of polygonal shapes as point collections
Andrea Alfieri, Yancong Lin, Jan van Gemert
ICCV Workshop (Best student paper!), 2021
arXiv

Exploit auto-regressive and parallel transformers in predicting collections of points (polygons).

Semi-Supervised Lane Detection with Deep Hough Transform
Yancong Lin, Silvia-Laura Pintea, Jan van Gemert
ICIP, 2021
Code / arXiv

Exploit lane representations in the Hough space from unlabel data.

Deep Hough Transform Line Priors
Yancong Lin, Silvia-Laura Pintea, Jan van Gemert
ECCV, 2020
Code / arXiv

Reduce data dependency by adding line priors through a trainable Hough transform module.

Quality Index for Stereoscopic Images by Jointly Evaluating Cyclopean Amplitude and Cyclopean Phase
Yancong Lin, Jiachen Yang, Wen Lu, Qinggang Meng, Zhihan Lv, Houbing Song
IEEE Journal of Selected Topics in Signal Processing, 2016

Stereo image quality assessment using binocular vision models and low-level features.

Core contribution of master thesis.

Experience

Reviewer: CVPR/ICCV/ECCV, IEEE Transactions on Image Processing.

Teaching Assistant: CS4245 Computer Vision by Deep Learning, 2019/2020 Q4.

Teaching Assistant: IN4393 Computer Vision, 2018/19 Q3.

Project: Real-time display of 3D scenes from 16 cameras (30 FPS, 1920 × 1080), 2016.

Internship: Institute of Automation, Chinese Academy of Science, Beijing, 07/2016–10/2016.

Awards/Skills

Awards: National Scholarship, Ministry of Education, 2016.

Skills: Python, C++, CUDA.

Miscellaneous

Fitness / Formula 1 / Premier League / NBA


Template from Jon Barron.