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The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task

Publications associées (28)

Context-Aware Image Super-Resolution Using Deep Neural Networks

Image super-resolution is a classic ill-posed computer vision and image processing problem, addressing the question of how to reconstruct a high-resolution image from its low-resolution counterpart. Current state-of-the-art methods have improved the perfor ...

EPFL2021

Semantics-Aware Spatial-Temporal Binaries for Cross-Modal Video Retrieval

Jie Luo, Yiyu Wang, Mengshi Qi

With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent ...

2021

Defect segmentation for multi-illumination quality control systems

Pascal Fua, Engin Türetken, Siavash Arjomand Bigdeli, David Honzátko

Thanks to recent advancements in image processing and deep learning techniques, visual surface inspection in production lines has become an automated process as long as all the defects are visible in a single or a few images. However, it is often necessary ...

2021

Pretraining boosts out-of-domain robustness for pose estimation

Mackenzie Mathis, Alexander Mathis, Steffen Schneider, Thomas Ray Biasi, Mert Yüksekgönül, Matthias Bethge

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

IEEE COMPUTER SOC2021

Non-Intrusive Speech Quality Assessment with Transfer Learning and Subject-specific Scaling

Paolo Prandoni, Milos Cernak, Natalia Nessler

In communication systems, it is crucial to estimate the perceived quality of audio and speech. The industrial standards for many years have been PESQ, 3QUEST, and POLQA, which are intrusive methods. This restricts the possibilities of using these metrics i ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Multi-scale sequential network for semantic text segmentation and localization

Jean-Marc Odobez, Olivier Canévet, Michael Villamizar

We present a novel method for semantic text document analysis which in addition to localizing text it labels the text in user-defined semantic categories. More precisely, it consists of a fully-convolutional and sequential network that we apply to the part ...

2020

Graph-to-Graph Transformer for Transition-based Dependency Parsing

James Henderson, Alireza Mohammadshahi

We propose the Graph2Graph Transformer architecture for conditioning on and predicting arbitrary graphs, and apply it to the challenging task of transition-based dependency parsing. After proposing two novel Transformer models of transition-based dependenc ...

Association for Computational Linguistics2020

Idiap Submission to Swiss-German Language Detection Shared Task

Petr Motlicek

Language detection is a key part of the NLP pipeline for text processing. The task of automatically detecting languages belonging to disjoint groups is relatively easy. It is considerably challenging to detect languages that have similar origins or dialect ...

CEUR Workshop Proceedings2020