ALVR 2020

Invited Speakers

Schedule

Proceedings

Overview and Call For Papers

Language and vision research has attracted great attention from both natural language processing (NLP) and computer vision (CV) researchers, which is gradually shifting from passive perception, templated language and synthetic imagery/environments to active perception, natural language and photo-realistic simulation (or even real world). Thus far, few workshops on language and vision research have been organized by groups from the NLP community. We propose the first workshop on Advances in Language and Vision Research (ALVR) in order to promote the frontier of language and vision research and bring interested researchers together to discuss how to best tackle and solve real-world problems in this area.

This workshop covers (but is not limited to) the following topics:

• New tasks and datasets that provide real-world solutions in the intersection of NLP and CV;
• Language-guided interaction with the real world, e.g. navigation via instruction following or dialogue;
• External knowledge integration in visual and language understanding;
• Visually grounded multilingual study, e.g. multimodal machine translation;
• Shortcoming of existing language and vision tasks and datasets;
• Benefits of using multimodal learning in downstream NLP tasks;
• Self-supervised representation learning in language and vision;
• Transfer learning (including few/zero-shot learning) and domain adaptation;
• Cross-modal learning beyond image understanding, such as videos and audios;
• Multidisciplinary study that may involve linguistics, cognitive science, robotics, etc.

In addition, we will also hold the first Video-guided Machine Translation Challenge, which we refer to as VATEX Translation Challenge 2020. The challenge aims to initiate studies and benchmark progress towards models that can translate the source language into the target language with the assistance of spatiotemporal context in videos, based on our recently released large-scale multilingual video description dataset, VATEX. The VATEX dataset contains over 41,250 videos and 825,000 high-quality captions in both English and Chinese, half of which are English-Chinese translation pairs. Winners will be announced and awarded in the workshop.

Important Dates

Organizers and PC