mlsanityData to 7 Oct 2026

Steerable Transformers for Volumetric Data

arXiv 2405.15932 ↗First posted 24 May 2024cs.CVcited by 8

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Abstract (arXiv)

We introduce Steerable Transformers, an extension of the Vision Transformer mechanism that maintains equivariance to the special Euclidean group SE(d). We propose an equivariant attention mechanism that operates on features extracted by steerable convolutions. Operating in Fourier space, our network utilizes Fourier space non-linearities. Our experiments in both two and three dimensions show that adding steerable transformer layers to steerable convolutional networks enhances performance.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 40 of its 58 references that are in the map. First posted on arXiv 24 May 2024.

Builds on

40 of 58 references.

References · 40

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2017Graph Attention Networkscited by 8,854
  5. 2020End-to-End Object Detection with Transformerscited by 7,384
  6. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  7. 2016Group Equivariant Convolutional Networkscited by 1,154
  8. 2018Self-Attention with Relative Position Representationscited by 1,112
  9. 2018Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point cloudscited by 735
  10. 2020SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networkscited by 602
  11. 2019Stand-Alone Self-Attention in Vision Modelscited by 542
  12. 2018Spherical CNNscited by 452
28 more
  1. 2019General E(2)-Equivariant Steerable CNNscited by 441
  2. 2021Early Convolutions Help Transformers See Bettercited by 395
  3. 20183D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Datacited by 348
  4. 2017Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphscited by 307
  5. 2016Steerable CNNscited by 298
  6. 2018On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groupscited by 296
  7. 2016Harmonic Networks: Deep Translation and Rotation Equivariancecited by 293
  8. 2019Cormorant: Covariant Molecular Neural Networkscited by 262
  9. 2022Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphscited by 258
  10. 2018SO-Net: Self-Organizing Network for Point Cloud Analysiscited by 210
  11. 2023EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representationscited by 201
  12. 2017Learning Steerable Filters for Rotation Equivariant CNNscited by 193
  13. 2018Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Networkcited by 168
  14. 2016Generative and Discriminative Voxel Modeling with Convolutional Neural Networkscited by 128
  15. 2021Scalars are universal: Equivariant machine learning, structured like classical physicscited by 127
  16. 2023Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNscited by 113
  17. 2020LieTransformer: Equivariant self-attention for Lie Groupscited by 100
  18. 2016Rotation equivariant vector field networkscited by 98
  19. 2016TI-POOLING: transformation-invariant pooling for feature learning in Convolutional Neural Networkscited by 66
  20. 2020Group Equivariant Stand-Alone Self-Attention For Visioncited by 63
  21. 2020Attentive Group Equivariant Convolutional Networkscited by 62
  22. 2018CubeNet: Equivariance to 3D Rotation and Translationcited by 59
  23. 2020The general theory of permutation equivarant neural networks and higher order graph variational encoderscited by 28
  24. 2023E(2)-Equivariant Vision Transformercited by 27
  25. 2022SE(3)-Equivariant Attention Networks for Shape Reconstruction in Function Spacecited by 26
  26. 2016Orientation-boosted Voxel Nets for 3D Object Recognitioncited by 17
  27. 2016FusionNet: 3D Object Classification Using Multiple Data Representationscited by 12
  28. 2019Discrete Rotation Equivariance for Point Cloud Recognitioncited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 5.

8 papers.

  1. 2024Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structurescited by 20
  2. 2025Platonic Transformers: A Solid Choice For Equivariancecited by 9
  3. 2025Quick ViTs: Speeding up Vision Transformers through Equivariancecited by 3
  4. 2026Vanilla Group Equivariant Vision Transformer: Simple and Effectivecited by 3
  5. 2026Rotation Equivariant Mamba for Vision Taskscited by 1
  6. 2026LEPA: Learning Geometric Equivariance in Satellite Remote Sensing Data with a Predictive Architecturecited by 0
  7. 2026Tunable Soft Equivariance with Guaranteescited by 0
  8. 2026A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of O(2)cited by 0