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January 2024 – AI, Machine Learning & Data Science Meetup

Date & Time

Jan. 25, 2024, 1 p.m. - Jan. 25, 2024, 2:30 p.m.

Cost

$0

Location

Online


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Description

When

January 25, 2024 – 10:00 AM Pacific

Where

Virtual / Zoom - https://voxel51.com/computer-vision-events/jan-25-ai-machine-learning-data-science-meetup/

SANPO: A Scene Understanding, Accessibility, Navigation, Pathfinding, Obstacle Avoidance Dataset

In this talk we introduce SANPO, a large-scale egocentric video dataset focused on dense prediction in outdoor environments. It contains stereo video sessions collected across diverse outdoor environments, as well as rendered synthetic video sessions. To our knowledge, this is the first human egocentric video dataset with both large scale dense panoptic segmentation and depth annotations.

Speaker: Kimberly Wilber is a computer vision researcher at Google Research NYC. She previously studied tasks at the intersection of computer vision and crowdsourcing at Cornell Tech.

Setmlvis: Object Detection Comparison Using Set Visualization

We introduce Setmlvis, a novel tool employing set theory and visualization for object detection model comparison. It efficiently aggregates and matches detection data across multiple models, highlighting where models align or diverge in object detection. This approach allows for analysis of each model’s unique capabilities and common strengths. Through our system, we demonstrate how set theory and visualization can be used as a valuable asset in the model evaluation process.

Speaker: Liudas Panavas is a CS PhD student at Northeastern University’s Data Visualization Lab, where they focus on explainable AI for object detection algorithms. They specialize in developing visual analytics software and conducting comprehensive user experience evaluations.

Don’t Forget

  • Voxel51 will make a donation on behalf of the Meetup members to the charity that gets the most votes this month.

  • Can’t make the date and time? No problem! Just make sure to register here so we can send you links to the playbacks.