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Achieving state-of-the-art results in pose estimation, this method leverages symmetry-aware features to simplify the complexities of rotation learning in a non-linear space.
Achieve state-of-the-art point cloud processing accuracy with HPENets while slashing FLOPs by up to 79% compared to PointNeXt by using high-dimensional positional encoding and non-local MLPs.
