mlsanityData to 14 Oct 2026

Generalizable Implicit Neural Representations via Instance Pattern Composers

arXiv 2211.13223 ↗First posted 23 Nov 2022cs.CV cs.LGcited by 39

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Abstract (arXiv)

Despite recent advances in implicit neural representations (INRs), it remains challenging for a coordinate-based multi-layer perceptron (MLP) of INRs to learn a common representation across data instances and generalize it for unseen instances. In this work, we introduce a simple yet effective framework for generalizable INRs that enables a coordinate-based MLP to represent complex data instances by modulating only a small set of weights in an early MLP layer as an instance pattern composer; the remaining MLP weights learn pattern composition rules for common representations across instances. Our generalizable INR framework is fully compatible with existing meta-learning and hypernetworks in learning to predict the modulated weight for unseen instances. Extensive experiments demonstrate that our method achieves high performance on a wide range of domains such as an audio, image, and 3D object, while the ablation study validates our weight modulation.

Key facts. Cited by 39 papers in the map (data through 14 Oct 2026). Builds on 26 of its 34 references that are in the map. First posted on arXiv 23 Nov 2022.

Builds on

26 of 34 references.

References · 26

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  3. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 30,186
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14 more
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  4. 2021NeRV: Neural Representations for Videoscited by 256
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  6. 2021COIN: COmpression with Implicit Neural representationscited by 233
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  11. 2022Transformers as Meta-Learners for Implicit Neural Representationscited by 79
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Citing papers per year: 2023: 3; 2024: 10; 2025: 14; 2026: 12.

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  1. 2024Online Adaptation of Language Models with a Memory of Amortized Contextscited by 35
  2. 2023Locality-Aware Generalizable Implicit Neural Representationcited by 16
  3. 2024Generalizable Implicit Motion Modeling for Video Frame Interpolationcited by 16
  4. 2024CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equationscited by 14
  5. 2024Learning Transferable Features for Implicit Neural Representationscited by 14
  6. 2023Learning Large-scale Neural Fields via Context Pruned Meta-Learningcited by 13
  7. 2023NVS-Adapter: Plug-and-Play Novel View Synthesis from a Single Imagecited by 11
  8. 2024Fast Encoding and Decoding for Implicit Video Representationcited by 11
  9. 2024Latent-INR: A Flexible Framework for Implicit Representations of Videos with Discriminative Semanticscited by 9
  10. 2025Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Modelscited by 7
  11. 2024Attention Beats Linear for Fast Implicit Neural Representation Generationcited by 6
  12. 2024Explaining the Implicit Neural Canvas: Connecting Pixels to Neurons by Tracing their Contributionscited by 5
27 more
  1. 2024Neural Fourier Modelling: A Highly Compact Approach to Time-Series Analysiscited by 3
  2. 2024INRetouch: Context Aware Implicit Neural Representation for Photography Retouchingcited by 3
  3. 2025How to Design and Train Your Implicit Neural Representation for Video Compressioncited by 3
  4. 2025SIEDD: Shared-Implicit Encoder with Discrete Decoderscited by 2
  5. 2025Spectral Bottleneck in Sinusoidal Representation Networks: Noise is All You Needcited by 2
  6. 2026Disentangled Learning Improves Implicit Neural Representations for Medical Reconstructioncited by 2
  7. 2025HyperNVD: Accelerating Neural Video Decomposition via Hypernetworkscited by 1
  8. 2025Meta-Continual Learning of Neural Fieldscited by 1
  9. 2025MINR: Implicit Neural Representations with Masked Image Modellingcited by 1
  10. 2025FedMeNF: Privacy-Preserving Federated Meta-Learning for Neural Fieldscited by 1
  11. 2025Improving Accuracy and Efficiency of Implicit Neural Representations: Making SIREN a WINNERcited by 1
  12. 2025CryoHype: Reconstructing a thousand cryo-EM structures with transformer-based hypernetworkscited by 1
  13. 2026Implicit Neural Representation Facilitates Unified Universal Vision Encodingcited by 1
  14. 2026Ensuring Semantics in Weights of Implicit Neural Representations through the Implicit Function Theoremcited by 1
  15. 2026TeCoNeRV: Leveraging Temporal Coherence for Compressible Neural Representations for Videoscited by 1
  16. 2026The Surprising Effectiveness of Noise Pretraining for Implicit Neural Representationscited by 1
  17. 2025Collaborative Imputation of Urban Time Series through Cross-city Meta-learningcited by 0
  18. 2025Geometric Neural Process Fieldscited by 0
  19. 2025Generalizable Implicit Neural Representations via Parameterized Latent Dynamics for Baroclinic Ocean Forecastingcited by 0
  20. 2025NeRV-Diffusion: Diffuse Implicit Neural Representations for Video Synthesiscited by 0
  21. 2026Don't Mind the Gaps: Implicit Neural Representations for Resolution-Agnostic Retinal OCT Analysiscited by 0
  22. 2026SAND: Spatially Adaptive Network Depth for Fast Sampling of Neural Implicit Surfacescited by 0
  23. 2026What Cohort INRs Encode and Where to Freeze Themcited by 0
  24. 2026Rethinking Amortized Neural Representations for High-Resolution Terrain Elevation Datacited by 0
  25. 2026HyperGS: Fast and Generalizable Gaussian Video Representationcited by 0
  26. 2026Weight-Space Mixture-of-Experts for Implicit Neural Representation Classificationcited by 0
  27. 2026CoANeRV: Coordinate-Aware Token-Space Neural Video Representationcited by 0