Researchers from Columbia University and Deepmind Introduce GPAT: A Transformer-Based Model Architecture that Accurately Predicts Part Poses by Inferring How Each Part Shape Corresponds to the Target Shape

Autonomous robotic systems capable of assembling new objects through visuospatial reasoning hold great potential for a broad range of real-world applications. Despite remarkable advancements in part assembly, existing approaches remain limited to pre-defined targets or familiar categories. To address this limitation, a joint research team from Columbia University and Google DeepMind introduces the General Part […]

The post Researchers from Columbia University and Deepmind Introduce GPAT: A Transformer-Based Model Architecture that Accurately Predicts Part Poses by Inferring How Each Part …

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