Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation
S. Jenni, and P. Favaro. "Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation." In ACCV 2020.
PhD in Computer Science - University of Bern, 2017-present
Topics: Analysis and design of self-supervised learning methods
Advisor: Prof. Paolo Favaro
MSc in Computer Science - University of Bern, 2017
With specialization in Advanced Information Processing – summa cum laude
Thesis Title: From Cartoons to Real Images: An Approach to Unsupervised Visual Representation Learning
BSc in Computer Science - University of Bern, 2015
With minors in Mathematics (60 ECTS) and Physics (30 ECTS) – magna cum laude
Thesis Title: A Study of 3D Deformable Parts Models for Detection and Pose-Estimation
Junior Data Analyst - Philip Morris International, 2016
Development of a Matlab tool for the automatic analysis of ciliary beating videos. The tool extracts key features such as tissue activity and main beating frequency with higher accuracy than prior methods.
Software Engineering Intern - AdNovum, 2015
I worked on a mobile payment app, implementing several parts of the iOS version in Objective-C.
S. Jenni, and P. Favaro. "Self-Supervised Multi-View Synchronization Learning for 3D Pose Estimation." In ACCV 2020.
S. Jenni, G. Meishvili, and P. Favaro. "Video Representation Learning by Recognizing Temporal Transformations." In ECCV 2020.
S. Jenni, H. Jin, and P. Favaro. "Steering Self-Supervised Feature Learning Beyond Local Pixel Statistics." In CVPR 2020.
G.Meishvili, S. Jenni, and P. Favaro. "Learning to Have an Ear for Face Super-Resolution." In CVPR 2020.
S. Jonas, A. Rossetti, M. Oddo, S. Jenni, P. Favaro and F. Zubler. "EEG-based Outcome Prediction after Cardiac Arrest with Convolutional Neural Networks: Performance and Visualization of Discriminative Features." In HBM 2019.
S. Jenni, and P. Favaro. "On Stabilizing Generative Adversarial Training with Noise." In CVPR 2019.
S. Jenni, and P. Favaro. "Deep Bilevel Learning." In ECCV 2018.
S. Jenni, and P. Favaro. "Self-Supervised Feature Learning by Learning to Spot Artifacts." In CVPR 2018.
Joint Alumni Association in Computer Science (JAACS):
Award for the best Master Thesis in Computer Science (2017)
P.A.I.S.S. Best Poster Award:
Award for the poster on “Self-Supervised Feature Learning by Learning to Spot Artifacts” (2018)
Paper Reviewing Recognitions:
CVPR, outstanding reviewer (2019)
ECCV, top reviewer (2020)
Programming Languages:
Python, MATLAB/Octave, Java, Objective-C, LaTeX
Frameworks:
Tensorflow, PyTorch, Caffe, SciPy, Numpy, OpenCV
Languages:
German (native), English (fluent), French