Songyou Peng - Homepage

Songyou Peng (彭崧猷)

I completed an Erasmus Mundus Masters in Computer Vision and Robotics (VIBOT) with distinction. During the master, I was fortunate to be supervised by Daniel Cremers at Technical University of Munich for my thesis and work with Peter Sturm at INRIA for two summers. Before this, I obtained a Bachelors in Automation at Xi'an Jiaotong University.

I have also spent some time at ADSC and A*STAR in Singapore.

News

05/2022 Selected as an outstanding reviewer at CVPR 2022.
03/2022 Our paper NICE-SLAM is accepted to CVPR 2022!
02/2022 Invited to talk about Shape As Points at Talking Papers Podcast. Great chat with Yizhak Ben-Shabat!
12/2021 Gave a talk again this year at GAMES Seminar Series on Shape As Points.
09/2021 Our Shape As Points is accepted to NeurIPS 2021 as oral presentation (top 0.6%)!
08/2021 Join Facebook Reality Labs (FRL) as a research intern this fall.
07/2021 Two papers (UNISURF and KiloNeRF) are accepted to ICCV 2021!
06/2021 Gave a talk at GAMES Seminar Series on Towards Practical Applications of NeRF.

Research

NICE-SLAM: Neural Implicit Scalable Encoding for SLAM
Zihan Zhu*, Songyou Peng*, Viktor Larsson, Weiwei Xu, Hujun Bao, Zhaopeng Cui, Martin R. Oswald, Marc Pollefeys
Conference on Computer Vision and Pattern Recognition (CVPR), 2022
(* equal contribution)
paper | project page | video | code

A neural implicit-based RGB-D SLAM that can be applied to large-scale scenes.

An interpretable hybird shape representation that yields HQ watertight meshes at low inference times.

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction
Michael Oechsle, Songyou Peng, Andreas Geiger
International Conference on Computer Vision (ICCV), 2021 (Oral, top 3%)
paper | project page | video | teaser video | code

Our method enables to reconstruct accurate surfaces without input masks.

Over 2000x speed-ups for NeRF are possible by utilizing thousands of tiny MLPs.

Dynamic Plane Convolutional Occupancy Networks
Stefan Lionar*, Daniil Emtsev*, Dusan Svilarkovic*, Songyou Peng
Winter Conference on Applications of Computer Vision (WACV), 2021
(* equal contribution)
paper | video | code

A student project of 3D Vision course at ETH Zurich where I served as the advisor.

A flexible implicit representation for accurate large-scale 3D reconstruction.

DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracing
Shaohui Liu, Yinda Zhang, Songyou Peng, Boxin Shi, Marc Pollefeys, Zhaopeng Cui
Conference on Computer Vision and Pattern Recognition (CVPR), 2020
paper | project page | teaser video | poster | code

A differentiable renderer for deep implicit signed distance functions.

Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty
Songyou Peng and Peter Sturm
International Conference on Computer Vision (ICCV), 2019 (Oral, top 4.6%)
paper | video | poster | code

A novel system that interactively guides a user to take optimal calibration images.

Photometric Depth Super-Resolution
Bjoern Haefner*, Songyou Peng*, Alok Verma*, Yvain Queau, Daniel Cremers
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019
(* equal contribution)
paper | project page

Recover high-resolution depth maps with fine geometric details using photometric techniques.

	PersEmoN: A Deep Network for Joint Analysis of Apparent Personality, Emotion and Their Relationship Le Zhang, Songyou Peng, Stefan Winkler IEEE Transactions on Affective Computing (TAFFC), 2019. In press. paper \| code A journal extension of our ACM MM 2018 paper.
	Give Me One Portrait Image, I Will Tell You Your Emotion and Personality Songyou Peng, Le Zhang, Stefan Winkler, Marianne Winslett ACM International Conference on Multimedia (ACM MM), 2018 paper \| slides \| code Technical Demo. A deep Siamese-like network is introduced to predict one's Big-Five personality and arousal-valence emotion from one portrait photo.
	Depth Super-Resolution Meets Uncalibrated Photometric Stereo Songyou Peng, Bjoern Haefner, Yvain Queau, Daniel Cremers International Conference on Computer Vision (ICCV) Workshops, 2017 paper \| slides \| code & data A novel depth super-resolution approach for RGB-D sensors is presented. This paper a part of my master thesis, and subsumed by our TPAMI paper.
	High Quality Shape from a RGB-D Camera using Photometric Stereo Songyou Peng M.Sc. Thesis, Techinical University of Munich Supervisor: Yvain Queau and Daniel Cremers thesis \| bibtex \| poster

Invited Talks

	Neural Scene Representations for 3D Reconstruction Songyou Peng University of Basel, 2022 slides
	Shape As Points: A Differentiable Poisson Solver Songyou Peng Talking Papers Podcast, 2022 video \| podcast
	Shape As Points: A Differentiable Poisson Solver Songyou Peng Graphics And Mixed Environment Seminar (GAMES), 2021 slides \| talk (in Chinese)
	Towards Practical Applications of NeRF Songyou Peng Graphics And Mixed Environment Seminar (GAMES), 2021 slides \| talk (in Chinese)

Selected Projects

1st for vision-only arousal/valence prediction and 2nd for overall valence prediction.

Apply visual SLAM on the Pepper robot along with object recognition.

Teaching

Teaching Assistant (Lead), 3D Vision, Spring 2022
Teaching Assistant, Deep Learning for Computer Vision: Seminal Work, Spring 2022
Teaching Assistant, 3D Vision, Spring 2020
Teaching Assistant, Deep Learning for Computer Vision: Seminal Work, Spring 2020

Teaching Assistant, Deep Learning, Winter 2020/2021

Academic Services

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Last updated: May 2022