mlsanityData to 7 Oct 2026

Deep Roto-Translation Scattering for Object Classification

arXiv 1412.8659 ↗First posted 30 Dec 2014cs.CVcited by 49

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Abstract (arXiv)

Dictionary learning algorithms or supervised deep convolution networks have considerably improved the efficiency of predefined feature representations such as SIFT. We introduce a deep scattering convolution network, with predefined wavelet filters over spatial and angular variables. This representation brings an important improvement to results previously obtained with predefined features over object image databases such as Caltech and CIFAR. The resulting accuracy is comparable to results obtained with unsupervised deep learning and dictionary based representations. This shows that refining image representations by using geometric priors is a promising direction to improve image classification and its understanding.

Key facts. Cited by 49 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Dec 2014.

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Citing papers per year: 2021: 10; 2022: 17; 2023: 14; 2024: 2; 2025: 5; 2026: 1.

49 papers.

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  1. 2022Unlocking High-Accuracy Differentially Private Image Classification through Scalecited by 218
  2. 2021Wavelet-Packets for Deepfake Image Analysis and Detectioncited by 25
  3. 2023Arbitrary Decisions are a Hidden Cost of Differentially Private Trainingcited by 19
  4. 2023Differentially Private Image Classification by Learning Priors from Random Processescited by 19
  5. 2023A Rainbow in Deep Network Black Boxescited by 18
  6. 2022Privacy-Aware Compression for Federated Data Analysiscited by 17
  7. 2022Leveraging Equivariant Features for Absolute Pose Regressioncited by 17
  8. 2023Unlocking Accuracy and Fairness in Differentially Private Image Classificationcited by 16
  9. 2021Parametric Scattering Networkscited by 15
  10. 2023DPMLBench: Holistic Evaluation of Differentially Private Machine Learningcited by 13
  11. 2022Conflicting Interactions Among Protection Mechanisms for Machine Learning Modelscited by 12
  12. 2021Spectral Leakage and Rethinking the Kernel Size in CNNscited by 11
37 more
  1. 2021The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methodscited by 8
  2. 2022Analysis of (sub-)Riemannian PDE-G-CNNscited by 8
  3. 2021Deformation Robust Roto-Scale-Translation Equivariant CNNscited by 7
  4. 2021Equivariant Wavelets: Fast Rotation and Translation Invariant Wavelet Scattering Transformscited by 6
  5. 2021Towards Understanding Theoretical Advantages of Complex-Reaction Networkscited by 6
  6. 2022Minimalistic Unsupervised Learning with the Sparse Manifold Transformcited by 6
  7. 2023Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filteringcited by 6
  8. 2024Attack-Aware Noise Calibration for Differential Privacycited by 6
  9. 2022Self-Supervised Pretraining for Differentially Private Learningcited by 4
  10. 2023Riesz feature representation: scale equivariant scattering network for classification taskscited by 4
  11. 2022Adversarial Audio Synthesis with Complex-valued Polynomial Networkscited by 3
  12. 2023Convolutional Networks with Oriented 1D Kernelscited by 3
  13. 2022NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data Releasecited by 2
  14. 2022On the Shift Invariance of Max Pooling Feature Maps in Convolutional Neural Networkscited by 2
  15. 2022A Simple Strategy to Provable Invariance via Orbit Mappingcited by 2
  16. 2023Equivariant and Steerable Neural Networks: A review with special emphasis on the symmetric groupcited by 2
  17. 2023Wavelets Beat Monkeys at Adversarial Robustnesscited by 2
  18. 2021FILTRA: Rethinking Steerable CNN by Filter Transformcited by 1
  19. 2022Efficient Hybrid Network: Inducting Scattering Featurescited by 1
  20. 2022CoShNet: A Hybrid Complex Valued Neural Network using Shearletscited by 1
  21. 2023Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillationcited by 1
  22. 2023Deep learning in medical image registration: introduction and surveycited by 1
  23. 2023H-NeXt: The next step towards roto-translation invariant networkscited by 1
  24. 2025Bottom-Up Scattering Information Perception Network for SAR target recognitioncited by 1
  25. 2025The Maximal Overlap Discrete Wavelet Scattering Transform and Its Application in Classification Taskscited by 1
  26. 2021CXR-Net: An Artificial Intelligence Pipeline for Quick Covid-19 Screening of Chest X-Rayscited by 0
  27. 2021Interferometric Graph Transform for Community Labelingcited by 0
  28. 2022Complexity from Adaptive-Symmetries Breaking: Global Minima in the Statistical Mechanics of Deep Neural Networkscited by 0
  29. 2022Survey on Self-supervised Representation Learning Using Image Transformationscited by 0
  30. 2022Algebraic Learning: Towards Interpretable Information Modelingcited by 0
  31. 2022From CNNs to Shift-Invariant Twin Models Based on Complex Waveletscited by 0
  32. 2023Affine Invariance in Continuous-Domain Convolutional Neural Networkscited by 0
  33. 2024P4: Towards private, personalized, and Peer-to-Peer learningcited by 0
  34. 2025Wavelet Scattering Transform and Fourier Representation for Offline Detection of Malicious Clients in Federated Learningcited by 0
  35. 2025Beyond Laplace and Gaussian: Exploring the Generalized Gaussian Mechanism for Private Machine Learningcited by 0
  36. 2025Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learningcited by 0
  37. 2026Rethinking Benchmarks for Differentially Private Image Classificationcited by 0