Invited Speakers


8:30-8:40 Opening remarks Workshop Organizers
8:40-9:15 Invited Talk
9:15-9:50 Invited Talk
9:50-10:10 VATEX Challenge
10:10-10:20 Challenge Talk [runner up]
10:20-10:30 Challenge Talk [winner]
10:30-11:00 Coffee Break and Poster Session
11:00-11:35 Invited Talk
11:35-12:10 Invited Talk
12:10-2:00 Lunch
2:00-2:35 Invited Talk
2:35-3:00 Invited Talk
3:10-3:30 Poster Highlights
3:30-4:00 Coffee Break and Poster Session
4:00-4:35 Invited Talk
4:35-5:10 Invited Talk
5:10-5:40 Panel Discussion



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:

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


  • Xin Wang
  • UC Santa Barbara
  • Jesse Thomason
  • University of Washington
  • Ronghang Hu
  • UC Berkeley
  • Xinlei Chen
  • Facebook AI Research
  • Peter Anderson
  • Georgia Tech
  • Qi Wu
  • Adelaide University
  • Asli Celikyilmaz
  • Microsoft Research
  • Jason Baldridge
  • Google Research
  • William Yang Wang
  • UC Santa Barbara

    Program Committee

  • Jacob Andreas
  • MIT
  • Angel Chang
  • Simon Fraser Univeristy
  • Devendra Chaplot
  • CMU
  • Abhishek Das
  • Georgia Tech
  • Daniel Fried
  • UC Berkeley
  • Zhe Gan
  • Microsoft
  • Christopher Kanan
  • Rochester Institute of Technology
  • Jiasen Lu
  • Georgia Tech
  • Ray Mooney
  • University of Texas, Austin
  • Khanh Nguyen
  • University of Maryland
  • Aishwarya Padmakumar
  • University of Texas, Austin
  • Alessandro Suglia
  • Heriot-Watt University
  • Jiawei Wu
  • UC Santa Barbara