Inverse Modeling Insights
Marius discusses the innovative approach of using synthetic data to train an inverse model that converts RGB images into URDFs. By procedurally generating simulation environments and leveraging stable diffusion, they create realistic datasets while ensuring depth information guides the image generation process. This method not only simplifies data acquisition but also enhances the model's ability to produce accurate real-world representations.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Bridging the Sim2real Gap in Robotics with Marius Memmel - 695
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