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VN-Transformer: Rotation-Equivariant Attention for Vector Neurons
Serge Assaad · Carlton Downey · Rami Al-Rfou · Nigamaa Nayakanti · Benjamin Sapp

Rotation equivariance is a desirable property in many practical applications such as motion forecasting and 3D perception, where it can offer benefits like sample efficiency, better generalization, and robustness to input perturbations.Vector Neurons (VN) is a recently developed framework offering a simple yet effective approach for deriving rotation-equivariant analogs of standard machine learning operations by extending one-dimensional scalar neurons to three-dimensional "vector neurons."We introduce a novel "VN-Transformer" architecture to address several shortcomings of the current VN models. Our contributions are:(i) we derive a rotation-equivariant attention mechanism which eliminates the need for the heavy feature preprocessing required by the original Vector Neurons models; (ii) we extend the VN framework to support non-spatial attributes, expanding the applicability of these models to real-world datasets; (iii) we derive a rotation-equivariant mechanism for multi-scale reduction of point-cloud resolution, greatly speeding up inference and training; (iv) we show that small tradeoffs in equivariance (epsilon-approximate equivariance) can yield large improvements in numerical stability and training robustness on accelerated hardware, and we bound the propagation of equivariance violations in our models.Finally, we apply our VN-Transformer to 3D shape classification and motion forecasting with compelling results.

Author Information

Serge Assaad (Duke University)
Carlton Downey (Waymo)
Rami Al-Rfou (Waymo Research)

Rami Al-Rfou received his PhD at Stony Brook University. He conducted his research on the application of deep learning in multilingual natural language processing with emphasis on languages with scarce resources. Currently, he focuses on modeling contextual cues for dialogue modeling. For more information check personal website (http://alrfou.com).

Nigamaa Nayakanti (Waymo)
Benjamin Sapp (Waymo)

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