mlsanityData to 7 Oct 2026

Deep Meta Functionals for Shape Representation

arXiv 1908.06277 ↗First posted 17 Aug 2019cs.CV cs.LGcited by 53

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Abstract (arXiv)

We present a new method for 3D shape reconstruction from a single image, in which a deep neural network directly maps an image to a vector of network weights. The network textcolorblackparametrized by these weights represents a 3D shape by classifying every point in the volume as either within or outside the shape. The new representation has virtually unlimited capacity and resolution, and can have an arbitrary topology. Our experiments show that it leads to more accurate shape inference from a 2D projection than the existing methods, including voxel-, silhouette-, and mesh-based methods. The code is available at: https://github.com/gidilittwin/Deep-Meta

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Aug 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 16; 2022: 14; 2023: 12; 2024: 5; 2025: 3; 2026: 3.

53 papers.

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  1. 2021Neural Fields in Visual Computing and Beyondcited by 539
  2. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  3. 2021HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editingcited by 208
  4. 2021CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesiscited by 149
  5. 2023A Brief Review of Hypernetworks in Deep Learningcited by 102
  6. 2021HyperInverter: Improving StyleGAN Inversion via Hypernetworkcited by 85
  7. 2021H3D-Net: Few-Shot High-Fidelity 3D Head Reconstructioncited by 81
  8. 2022E-NeRV: Expedite Neural Video Representation with Disentangled Spatial-Temporal Contextcited by 76
  9. 2021Aligning Latent and Image Spaces to Connect the Unconnectablecited by 70
  10. 2021Neural Surface Mapscited by 34
  11. 2021Recomposing the Reinforcement Learning Building Blocks with Hypernetworkscited by 33
  12. 2023Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mappingcited by 27
38 more
  1. 2022HyperTime: Implicit Neural Representation for Time Seriescited by 24
  2. 2022Controllable Dynamic Multi-Task Architecturescited by 21
  3. 2022Latent Partition Implicit with Surface Codes for 3D Representationcited by 21
  4. 2023HyperINR: A Fast and Predictive Hypernetwork for Implicit Neural Representations via Knowledge Distillationcited by 19
  5. 2022NeuForm: Adaptive Overfitting for Neural Shape Editingcited by 18
  6. 2022Federated Learning with Heterogeneous Architectures using Graph HyperNetworkscited by 17
  7. 2022ANISE: Assembly-based Neural Implicit Surface rEconstructioncited by 16
  8. 2022DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domainscited by 15
  9. 2024HyperFusion: A Hypernetwork Approach to Multimodal Integration of Tabular and Medical Imaging Data for Predictive Modelingcited by 15
  10. 2022SymmNeRF: Learning to Explore Symmetry Prior for Single-View View Synthesiscited by 13
  11. 2022Neural Convolutional Surfacescited by 9
  12. 2024Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generationcited by 9
  13. 2021Learning and Meshing from Deep Implicit Surface Networks Using an Efficient Implementation of Analytic Marchingcited by 8
  14. 2021Meta Internal Learningcited by 7
  15. 2022Semi-supervised Learning of Partial Differential Operators and Dynamical Flowscited by 6
  16. 2023LIST: Learning Implicitly from Spatial Transformers for Single-View 3D Reconstructioncited by 6
  17. 2021Learning Mesh Representations via Binary Space Partitioning Tree Networkscited by 5
  18. 2021Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labelscited by 4
  19. 2022Time Series Forecasting with Hypernetworks Generating Parameters in Advancecited by 4
  20. 2023Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functionscited by 4
  21. 2023InstantAvatar: Efficient 3D Head Reconstruction via Surface Renderingcited by 4
  22. 2023Population-size-Aware Policy Optimization for Mean-Field Gamescited by 3
  23. 2023A Review of Deep Learning-Powered Mesh Reconstruction Methodscited by 3
  24. 2023INFAMOUS-NeRF: ImproviNg FAce MOdeling Using Semantically-Aligned Hypernetworks with Neural Radiance Fieldscited by 3
  25. 2025HypeRL: Hypernetwork-Based Reinforcement Learning for Control of Parametrized Dynamical Systemscited by 3
  26. 20213D Meta-Segmentation Neural Networkcited by 2
  27. 2022Towards Confidence-guided Shape Completion for Robotic Applicationscited by 2
  28. 2022Automated Reconstruction of 3D Open Surfaces from Sparse Point Cloudscited by 1
  29. 2023HyperPose: Hypernetwork-Infused Camera Pose Localization and an Extended Cambridge Landmarks Datasetcited by 1
  30. 2023HyperEditor: Achieving Both Authenticity and Cross-Domain Capability in Image Editing via Hypernetworkscited by 1
  31. 2024Leveraging Adaptive Implicit Representation Mapping for Ultra High-Resolution Image Segmentationcited by 1
  32. 2024Implicit Neural Representation For Accurate CFD Flow Field Predictioncited by 1
  33. 2025HyDA: Hypernetworks for Test Time Domain Adaptation in Medical Imaging Analysiscited by 1
  34. 2026SirenFNO: Efficient and Full Frequency Learning of Fourier Neural Operatorscited by 1
  35. 2021HyperHyperNetworks for the Design of Antenna Arrayscited by 0
  36. 2021Robust MIMO Detection using Hypernetworks with Learned Regularizerscited by 0
  37. 2023IPVNet: Learning Implicit Point-Voxel Features for Open-Surface 3D Reconstructioncited by 0
  38. 2024MNeRV: A Multilayer Neural Representation for Videoscited by 0

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