Style Generalization

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (13 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• MRFP: Learning Generalizable Semantic Segmentation from Sim-2-Real with Multi-Resolution Feature Perturbation
  30 Nov 2023 1 repository listed
  Deep neural networks have shown exemplary performance on semantic scene understanding tasks on source domains, but due to the absence of style diversity during training, enhancing performance on unseen target domains…
• Integral Probability Metrics PAC-Bayes Bounds
  1 Jul 2022 1 repository listed Syntology ran 5 of 7 samples · 2 unverified · 7 pointer-only (licence)
  We present a PAC-Bayes-style generalization bound which enables the replacement of the KL-divergence with a variety of Integral Probability Metrics (IPM).
• Creative Flow+ Dataset
  1 Jun 2019 1 repository listed
  We present the Creative Flow+ Dataset, the first diverse multi-style artistic video dataset richly labeled with per-pixel optical flow, occlusions, correspondences, segmentation labels, normals, and depth.
• DLOW: Domain Flow for Adaptation and Generalization
  13 Dec 2018 1 repository listed
  In this work, we present a domain flow generation(DLOW) model to bridge two different domains by generating a continuous sequence of intermediate domains flowing from one domain to the other.
• Night-to-Day Image Translation for Retrieval-based Localization
  26 Sep 2018 1 repository listed Syntology ran 0 of 6 samples · 6 unverified
  We then compare the daytime and translated night images to obtain a pose estimate for the night image using the known 6-DOF position of the closest day image.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.