Methods › General › Loss Functions › Cycle Consistency Loss

Cycle Consistency Loss

448 papers tagged archive 2025-07-28

Introduced by Jun-Yan Zhu et al. in Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

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

Cycle Consistency Loss is a type of loss used for generative adversarial networks that performs unpaired image-to-image translation. It was introduced with the CycleGAN architecture. For two domains X and Y, we want to learn a mapping G : X →Y and F: Y →X. We want to enforce the intuition that these mappings should be reverses of each other and that both mappings should be bijections. Cycle Consistency Loss encourages F(G(x)) ≈x and G(F(y)) ≈y. It reduces the space of possible mapping functions by enforcing forward and backwards consistency:

ℒ_(cyc)(G, F) = 𝔼_(x ∼p_(data)(x))[||F(G(x)) - x||₁] + 𝔼_(y ∼p_(data)(y))[||G(F(y)) - y||₁]

PaperSourceSee Code · junyanz/pytorch-CycleGAN-and-pix2pix

Papers archive 2025-07-28

30 shown of 448, 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 306 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
Translation112
Image-to-Image Translation92
Image Generation50
Generative Adversarial Network49
Domain Adaptation42
Data Augmentation33
Semantic Segmentation30
Style Transfer30
Segmentation28
SSIM26
Computed Tomography (CT)16
Diagnostic15
Object Detection15
Unsupervised Domain Adaptation15
object-detection15
Denoising14
Super-Resolution14
Anatomy13
Image Segmentation13
Diversity11

Usage over time archive 2025-07-28

Papers per year tagged with Cycle Consistency Loss: 2017 to 2025, peak 79 79 0 2017: 11 papers 2017 2018: 36 papers 2018 2019: 58 papers 2019 2020: 79 papers 2020 2021: 62 papers 2021 2022: 66 papers 2022 2023: 58 papers 2023 2024: 53 papers 2024 2025: 25 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (448 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

Loss Functions

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