Browse State-of-the-Art › Video Style Transfer
Video Style Transfer
15 papers with code · 0 benchmarks · 1 dataset archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
1 dataset whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
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Parent tasks archive 2025-07-28
Most implemented papers archive 2025-07-28
15 shown of 15 papers with code (35 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.
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26 Jul 2018 9 repositories listedThese and our qualitative results ranging from small image patches to megapixel stylistic images and videos show that our approach better captures the subtle nature in which a style affects content.
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3 Jul 2018 8 repositories listedImage style transfer models based on convolutional neural networks usually suffer from high temporal inconsistency when applied to videos.
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8 Aug 2021 3 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 4 pointer-only (licence)Finally, the content feature is normalized so that they demonstrate the same local feature statistics as the calculated per-point weighted style feature statistics.
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23 Sep 2021 2 repositories listed Syntology ran 2 of 17 samples · 15 unverifiedWe present a method that decomposes, or "unwraps", an input video into a set of layered 2D atlases, each providing a unified representation of the appearance of an object (or background) over the video.
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26 Oct 2024 1 repository listed Syntology ran 0 of 12 samples · 12 unverifiedThis paper presents UniVST, a unified framework for localized video style transfer based on diffusion model.
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7 Oct 2023 1 repository listedCurrent state-of-the-art video-to-video translation models rely on having a video sequence or a single style image to stylize an input video.
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23 May 2023 1 repository listedRecent advances in text-to-image (T2I) diffusion models have enabled impressive image generation capabilities guided by text prompts.
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9 May 2023 1 repository listedLarge-scale text-to-video diffusion models have demonstrated an exceptional ability to synthesize diverse videos.
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22 Apr 2023 1 repository listed Syntology ran 4 of 12 samples · 8 unverified · 12 pointer-only (licence)Current arbitrary style transfer models are limited to either image or video domains.
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31 Mar 2023 1 repository listedContent affinity loss including feature and pixel affinity is a main problem which leads to artifacts in photorealistic and video style transfer.
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16 Mar 2023 1 repository listed Syntology ran 7 of 12 samples · 5 unverifiedWe also have a better zero-shot shape-aware editing ability based on the text-to-video model.
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22 Sep 2022 1 repository listedAlthough a series of successful portrait image toonification models built upon the powerful StyleGAN have been proposed, these image-oriented methods have obvious limitations when applied to videos, such as the fixed…
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11 Jul 2022 1 repository listed Syntology ran 2 of 2 samples · 0 unverifiedCCPL can preserve the coherence of the content source during style transfer without degrading stylization.
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23 Sep 2020 1 repository listedIn this article, we address the problem by jointly considering the intrinsic properties of stylization and temporal consistency.
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1 Jun 2019 1 repository listedWe 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.
Syntology lines on 6 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.
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