2023 VizWiz Grand Challenge Workshop

Overview

Our goal for this workshop is to educate researchers about the technological needs of people with vision impairments while empowering researchers to improve algorithms to meet these needs. A key component of this event will be to track progress on four dataset challenges, where the tasks are to answer visual questions, ground answers, detect salient objects, and recognize objects in few-shot learning scenarios. The second key component of this event will be a discussion about current research and application issues, including invited speakers from both academia and industry who will share their experiences in building today’s state-­of-the-­art assistive technologies as well as designing next-generation tools.

Examples of image annotation tasks for the four dataset challenges of salient object detection, few-shot object recognition, visual question answering, and answer grounding.

Important Dates

  • Thursday, January 12: challenge submissions announced
  • Friday, January 13 [9:00am Central Standard Time]: challenges go live
  • Friday, May 5 [9:00am Central Standard Time]: challenge submissions due
  • Friday, May 12 [9:00am Central Standard Time]: extended abstracts due
  • Wednesday, May 17 [5:59pm Central Standard Time]: notification to authors about decisions for extended abstracts
  • Monday, June 19: half-day workshop

Submissions

We invite two types of submissions:

Challenge Submissions

We invite submissions about algorithms for the four challenge tasks: the visual question answering challenge task, the answer grounding challenge, the salient object detection challenge, and the few-shot object recognition challenge. We accept submissions for algorithms that are not published, currently under review, and already published. The teams with the top-performing submissions will be invited to give short talks during the workshop.

Extended Abstracts

We invite submissions of extended abstracts on topics related to image captioning, visual question answering, visual grounding, salient object detection, few shot learning, and assistive technologies for people with visual impairments. Papers must be at most two pages (with references) and follow the CVPR formatting guidelines using the provided author kit. Reviewing will be single-blind and accepted papers will be presented as posters. We will accept submissions on work that is not published, currently under review, and already published. There will be no proceedings. Please send your extended abstracts to workshop@vizwiz.org.

Please note that we will require all camera-ready content to be accessible via a screen reader. Given that making accessible PDFs and presentations may be a new process for some authors, we will host training sessions beforehand to both educate and assist all authors to succeed in making their content accessible.

Program

Location:

Coming soon.

Schedule:

Coming soon.

Invited Speakers and Panelists:

A headshot of Xin (Eric) Wang, a man wearing a black suit and bow tie with short black hair, looking directly at the camera smiling.

Xin (Eric) Wang
Assistant Professor
University of
California, Santa Cruz

A photo of Thomas Reid, a man wearing in a gray shirt and  sunglasses, smiling.

Thomas Reid
Audio Producer
“Reid My Mind”

A photo of Haoran Qi who is standing by the beach with his arm open and a smile on his face, with short dark hair and wearing glasses and a striped T-shirt.

Haoran Qi
Software Engineer
Google Outlook

Poster List

Coming soon.

Organizers

Danna Gurari
University of Colorado Boulder

Potrait picture of Jeffrey Bigham

Jeffrey Bigham
Carnegie Mellon University, Apple

A photo of Ed Cutrell, a man with closely-cropped gray hair and a short beard with mustache, photographed on the Microsoft campus in Redmond, Wash., Thursday, January 9, 2020. Ed is wearing a black turtleneck and rimless glasses and is looking at the camera smiling.(Photo by Dan DeLong)

Ed Cutrell
Microsoft

Portrait picture of Abigale Stangl, a woman with long red hair wearing a gray sweater and glasses looking straight at the camera and smiling

Abigale Stangl
University of Washington

Portrait picture of Chongyan Chen, a woman with long black hair wearing a T-shirt and glasses looking straight at the camera and smiling

Chongyan Chen
University of Texas at Austin

A portrait of Samreen Anjum, a woman with long brown hair, wearing a gray sweater and a red scarf. She is looking at the camera and smiling.

Samreen Anjum
University of Colorado Boulder

Contact Us

For questions, comments, or feedback, please send them to Danna Gurari at danna.gurari@colorado.edu.