mlsanityData to 14 Oct 2026

Deep Learning on Implicit Neural Representations of Shapes

arXiv 2302.05438 ↗First posted 10 Feb 2023cs.CVcited by 63

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Abstract (arXiv)

Implicit Neural Representations (INRs) have emerged in the last few years as a powerful tool to encode continuously a variety of different signals like images, videos, audio and 3D shapes. When applied to 3D shapes, INRs allow to overcome the fragmentation and shortcomings of the popular discrete representations used so far. Yet, considering that INRs consist in neural networks, it is not clear whether and how it may be possible to feed them into deep learning pipelines aimed at solving a downstream task. In this paper, we put forward this research problem and propose inr2vec, a framework that can compute a compact latent representation for an input INR in a single inference pass. We verify that inr2vec can embed effectively the 3D shapes represented by the input INRs and show how the produced embeddings can be fed into deep learning pipelines to solve several tasks by processing exclusively INRs.

Key facts. Cited by 63 papers in the map (data through 14 Oct 2026). Builds on 77 of its 106 references that are in the map. First posted on arXiv 10 Feb 2023.

Builds on

77 of 106 references.

References · 77

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38 more
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50 most cited of 77 All 77 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 10; 2024: 20; 2025: 20; 2026: 13.

63 papers.

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  1. 2023Permutation Equivariant Neural Functionalscited by 70
  2. 2024Graph Neural Networks for Learning Equivariant Representations of Neural Networkscited by 59
  3. 2023Graph Metanetworks for Processing Diverse Neural Architecturescited by 57
  4. 2023Neural Functional Transformerscited by 52
  5. 2024Towards Scalable and Versatile Weight Space Learningcited by 41
  6. 2024Universal Neural Functionalscited by 26
  7. 2024Scale Equivariant Graph Metanetworkscited by 24
  8. 2024Grounding Continuous Representations in Geometry: Equivariant Neural Fieldscited by 19
  9. 2024Monomial Matrix Group Equivariant Neural Functional Networkscited by 17
  10. 2024Deep Linear Probe Generators for Weight Space Learningcited by 17
  11. 2024FancyVideo: Towards Dynamic and Consistent Video Generation via Cross-frame Textual Guidancecited by 15
  12. 2023RayDF: Neural Ray-surface Distance Fields with Multi-view Consistencycited by 12
38 more
  1. 2024Implicit-Zoo: A Large-Scale Dataset of Neural Implicit Functions for 2D Images and 3D Scenescited by 12
  2. 2023Set-based Neural Network Encoding Without Weight Tyingcited by 9
  3. 2023Neural Processing of Tri-Plane Hybrid Neural Fieldscited by 8
  4. 2023In Search of a Data Transformation That Accelerates Neural Field Trainingcited by 7
  5. 2025End-to-End Implicit Neural Representations for Classificationcited by 7
  6. 2024Connecting NeRFs, Images, and Textcited by 6
  7. 2024LLaNA: Large Language and NeRF Assistantcited by 6
  8. 2025Structure Is Not Enough: Leveraging Behavior for Neural Network Weight Reconstructioncited by 6
  9. 2025Geometry aware inference of steady state PDEs using Equivariant Neural Fields representationscited by 6
  10. 2023Deep Learning on Object-centric 3D Neural Fieldscited by 5
  11. 2024Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributionscited by 5
  12. 2024Physics-informed Neural Networks for Functional Differential Equations: Cylindrical Approximation and Its Convergence Guaranteescited by 5
  13. 2025Weight-Space Linear Recurrent Neural Networkscited by 5
  14. 2024Neural Metamorphosiscited by 4
  15. 2023Text-guided Image-and-Shape Editing and Generation: A Short Surveycited by 3
  16. 2024Neural Video Representation for Redundancy Reduction and Consistency Preservationcited by 3
  17. 2025ARC: Anchored Representation Clouds for High-Resolution INR Classificationcited by 3
  18. 2025A Model Zoo on Phase Transitions in Neural Networkscited by 3
  19. 2026Deep Sketch-Based 3D Modeling: A Surveycited by 3
  20. 2024Transport of Algebraic Structure to Latent Embeddingscited by 2
  21. 2024Diff-INR: Generative Regularization for Electrical Impedance Tomographycited by 2
  22. 2025Few-shot Implicit Function Generation via Equivariancecited by 2
  23. 2025Neural Functions for Learning Periodic Signalcited by 2
  24. 2025Meta-learning Structure-Preserving Dynamicscited by 2
  25. 2024SpikeMM: Flexi-Magnification of High-Speed Micro-Motionscited by 1
  26. 2024Selective Test-Time Adaptation for Unsupervised Anomaly Detection using Neural Implicit Representationscited by 1
  27. 2025Boosting 3D Liver Shape Datasets with Diffusion Models and Implicit Neural Representationscited by 1
  28. 2025NeuroVoxel-LM: Language-Aligned 3D Perception via Dynamic Voxelization and Meta-Embeddingcited by 1
  29. 2026Ensuring Semantics in Weights of Implicit Neural Representations through the Implicit Function Theoremcited by 1
  30. 2026Quasi-Equivariant Metanetworkscited by 1
  31. 2026Monocular Avatar Reconstruction via Cascaded Diffusion Priors and UV-Space Differentiable Shadingcited by 1
  32. 2026Dynamic Neural Graph Encoding of Inference Processes in Deep Weight Spacecited by 1
  33. 2023Contextualising Implicit Representations for Semantic Taskscited by 0
  34. 2024Hyper-Representations: Learning from Populations of Neural Networkscited by 0
  35. 2025MorphoSkel3D: Morphological Skeletonization of 3D Point Clouds for Informed Sampling in Object Classification and Retrievalcited by 0
  36. 2025INRet: A General Framework for Accurate Retrieval of INRs for Shapescited by 0
  37. 2025Can We Optimize Deep RL Policy Weights as Trajectory Modeling?cited by 0
  38. 2025On the Internal Representations of Graph Metanetworkscited by 0

50 most cited of 63 All 63 (JSON)