for 2D human face pose estimation or something,” he explains. “We’re trying to solve problems, and we’re trying to define the problems as well, like with the Multiple Toddler Tracking in Indoor Videos paper. What are the important things to pay attention to? What’s dangerous to safety? What’s of interest to the parents?” Elaheh adds: “What makes this workshop unique is its strong backbone. We’re not just bringing part of the lab; we’re bringing our collaborators. The regular open problem in computer vision is that we have a dataset, and people come and make some improvements on top of an already developed method. However, we studied different problems in the domains and worked on the building blocks of this ourselves. It will be good to show people the challenges we faced, all the open problems. We sometimes didn’t even have small data and were working toward that. We believe it will have a huge impact on the whole computer vision community. We’re so excited to share it with the rest of the world! Who can say they don’t care about infants and endangered animals?” Another important emphasis of the event is on the positive applications of AI amidst current concerns about its potential negative impact. For example, AI tools that could detect and monitor the early signs of autism or torticollis. These conditions could then be addressed or rehabilitated sooner. “That would have a cascading positive effect on people’s lives,” Sarah says. “Rather than just talking about the scariness of AI, I think now is a good time for these two 25 DAILY WACV Friday CV4Smalls SPAC-Net: An overview architecture of our synthetic prior-aware animal ControlNet (SPAC-Net), composed of three parts: pose augmentation, style transfer and dataset generation. The SPAC-Net pipeline leads to generation of our probabilistically-valid animal SPAC-Animals dataset.
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