Workshop program

Sept. 9, 2018, 9 a.m. 9:30-17:00

The workshop will take place at Holiday Inn Munich – City Centre, Hochstrasse 3, 81669 München, Germany.


Full-day workshop

 9:30 –   9:45 Opening of the Workshop

 9:45 – 10:30 First invited talk, Nadine Peyrieras, Institut des Neurosciences Paris-Saclay.

Session chair: Sergio Escalera (9.30-10:30)

10:30 – 11:00 Coffee break

11:00 – 11:30 Second invited talk, Philipp Krähenbühl, University of Texas at Austin.

11:30 - 12:30 Worshop presentations, Fingerprint competition:

FPD-M-net: Fingerprint Image Denoising and Inpainting Using M-Net Based Convolutional Neural Networks, Sukesh Adiga V and Jayanthi Sivaswamy

Iterative application of autoencoder for video inpainting and fingerprint denoising, Le Manh Quan, Yong-Guk Kim

U-Finger: Multi-Scale Dilated Convolutional Network for Fingerprint Image Denoising and Inpainting, Ramakrishna Prabhu, Xiaojing Yu, Zhangyang Wang, Ding Liu, Anxiao (Andrew) Jiang

Deep End-to-end Fingerprint Denoising and Inpainting, Youness Mansar

Session chair: Meysam Madadi (11.00-12:30)

12:30 – 14:00 Lunch Sponsored by chalearn

14:00 – 14:45 Third invited talk, Eli Shechtman, Adobe.

14:45 – 15:30 Workshop presentations, Decaptioning competition:

DVDNet: Deep Blind Video Decaptioning with 3D-2D Gated Convolutions, Dahun Kim, Sanghyun Woo, Joon-Young Lee, In So Kweon

Joint Caption Detection and Inpainting using Generative Network, Anubha Pandey, Vismay Patel

Video DeCaptioning using U-Net with Stacked Dilated Convolutional Layers, Shivansh Mundra, Sayan Sinha, Mehul Kumar Nirala, and Arnav Jain

Session chair: Marc Oliu (14:00-15:30)

15:30 – 16:00 Coffee break

16:00 – 16:30 Fourth invited talk, Guanbin Li, Sun Yat-sen University.

Title: Deep context modeling for image and video restoration
Abstract: Image restoration is the foundation of low-level computer vision task. The solution of this problem is crucial for image content editing and the enhancement of semantic visual understanding. Recently, Convolutional Neural Networks (CNNs) have greatly advanced the performance in several tasks of image restoration, including but not limited to image super-resolution, inpainting, denoising, etc. In this talk, I will introduce different deep learning based context modelling frameworks for three visual restoration tasks, including single image completion, video super-resolution and image de-raining.

16:30 – 16:45 Workshop presentations, Image inpainting for human pose competition:

Generative Image Inpainting for Person Pose Generation, Anubha Pandey, Vismay Patel

16:45 – 17:00 Workshop presentations:

Road layout understanding by generative adversarial inpainting, Lorenzo Berlincioni, Federico Becattini, Leonardo Galteri, Lorenzo Seidenari, Alberto Del Bimbo

17:00 – 17:30 Fifth invited talk, Ming-Yu Liu, NVIDIA

Session chair: Ciprian Corneanu (16:00-17:30)

17:30 – 17:35 Closing


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