Methods › General › Self-Supervised Learning › Inpainting

Inpainting

998 papers tagged archive 2025-07-28

Introduced by Deepak Pathak et al. in Context Encoders: Feature Learning by Inpainting

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Train a convolutional neural network to generate the contents of an arbitrary image region conditioned on its surroundings.

PaperSource

Papers archive 2025-07-28

30 shown of 998, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 444 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Inpainting361
Image Generation113
Denoising108
Video Inpainting90
Object70
Semantic Segmentation47
Decoder39
Image Restoration37
Segmentation37
Super-Resolution36
Novel View Synthesis31
NeRF29
Optical Flow Estimation29
Generative Adversarial Network27
Diversity26
Data Augmentation24
Facial Inpainting23
Image Reconstruction21
Virtual Try-on21
Depth Estimation19

Usage over time archive 2025-07-28

Papers per year tagged with Inpainting: 2016 to 2025, peak 331 331 0 2016: 1 paper 2016 2017: 0 papers 2017 2018: 0 papers 2018 2019: 0 papers 2019 2020: 38 papers 2020 2021: 121 papers 2021 2022: 153 papers 2022 2023: 220 papers 2023 2024: 331 papers 2024 2025: 134 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (998 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Self-Supervised Learning

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