Abstract: Unpaired shape-to-shape translation refers to the task of transforming the geometry and semantics of an input shape into a new shape domain without paired training data. Previous methods ...

Note: We have recently found that Dora-VAE can specify tokens of any length during inference, even if this length has not been seen during training. During inference, you could use a latent code ...

Figure 1. StructureNet is a hierarchical graph network that produces a unified latent space to encode structured models with both continuous geometric and discrete structural variations. In this ...

Abstract: Reliable object grasping is a crucial capability for autonomous robots. However, many existing grasping approaches focus on general clutter removal without explicitly modeling objects and ...

Same as traditional autoencoders, VAE architecture has two parts: an encoder and a decoder. Traditional AE models map inputs into a latent-space vector and reconstruct the output from this vector. VAE ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Machine learning has been successfully applied in recent years to screen materials for ...

Progress in AI systems often feels cyclical. Every few years, computers can suddenly do something they’ve never been able to do before. “Behold!” the AI true believers proclaim, “the age of artificial ...

The hippocampus is thought to enable the encoding and retrieval of ongoing experience, the organization of that experience into structured representations like contexts, maps, and schemas, and the use ...