Methods › Computer Vision › Image Super-Resolution Models › PULSE

PULSE

5 papers tagged archive 2025-07-28

Introduced by Sachit Menon et al. in PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models

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

PULSE is a self-supervised photo upsampling algorithm. Instead of starting with the LR image and slowly adding detail, PULSE traverses the high-resolution natural image manifold, searching for images that downscale to the original LR image. This is formalized through the downscaling loss, which guides exploration through the latent space of a generative model. By leveraging properties of high-dimensional Gaussians, the authors aim to restrict the search space to guarantee realistic outputs.

PaperSource

Papers archive 2025-07-28

5 shown of 5, 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

10 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
Super-Resolution2
Denoising1
Diagnostic1
Face Hallucination1
Hallucination1
Heart rate estimation1
Image Comprehension1
Image Super-Resolution1
Photoplethysmography (PPG)1
compressed sensing1

Usage over time archive 2025-07-28

Papers per year tagged with PULSE: 2020 to 2024, peak 1 1 0 2020: 1 paper 2020 2021: 1 paper 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (5 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

Image Super-Resolution Models

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