Vernata: ETH Zurich's multi-teacher distillation for self-supervised LiDAR representations, IROS 2026
rsasaki0109 · x · 2026-10-12
Robotics and AI Institute and ETH Zurich released Vernata, a multi-modal, multi-teacher distillation framework for self-supervised learning on outdoor LiDAR point clouds, accepted at IROS 2026 and open-sourced under MIT license. Building on Sonata, it adds sparse view augmentation, a memory bank mechanism, and cross-modal distillation from dense high-resolution 2D image features for fine-grained semantic guidance and robust inference across varying point densities. The architecture combines Global/Masked/Local/Sparse views with an EMA teacher, Sinkhorn-Knopp normalization, and joint cross-entropy plus cosine similarity losses.
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