Interactive Photo Editing on Smartphones via Intrinsic Decomposition

Shekhar, Sumit; Reimann, Max; Mayer, Maximilian; Semmo, Amir; Pasewaldt, Sebastian; Döllner, Jürgen; Trapp, Matthias

doi:10.1111/cgf.142650

Cited by 7 publications

(8 citation statements)

References 71 publications

(84 reference statements)

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“…Our local consistency component comprising a convex combination of temporal neighbors can be seen as a crude form of local temporal denoising. Previously it has been shown that temporal denoising is effective in enforcing consistency [SST * 19]. We conjecture that efficient temporal denoising combined with flow‐based warping can further improve temporal stabilization not only for stylization but also for other tasks.…”

Section: Discussionmentioning

confidence: 76%

“…It was interesting to observe that for certain cases the method of Bonneel et al which degrades the processed style significantly was still preferred by users over others due to its high consistency quality. We also show subjective user preference for our method over the methods of Shekhar et al [SST * 19] and Thimonier et al [TDKP21] via another user study in the supplementary material. Shekhar et al which is completely based on temporal denoising is prone to introduce motion blur artifacts and is less efficient in terms of enforcing global consistency.…”

Section: Discussionmentioning

confidence: 85%

“…To further improve consistency, one can warp more neighboring frames around the current time instance t. As we increase the temporal window size for such an adaptive combination it has a denoising effect leading to further reduction in flickering. The temporal denoising performed by Shekhar et al [SST * 19], for enforcing consistency, can be considered as a specific example of the above scenario. However, for interactive stylization, warping more frames to the current instance is not feasible due to time constraints.…”

Section: Methodsmentioning

confidence: 99%

“…1) or do not provide interactive consistency control [LHW * 18,TDKP21], which is an essential requirement for artistic rendering [FLJ * 14]. Currently, the only method that provides interactive consistency control is limited to offline processing and requires preprocessing [SST * 19].…”

Section: Introductionmentioning

confidence: 99%

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Interactive Control over Temporal Consistency while Stylizing Video Streams

Shekhar

Reimann

Hilscher

et al. 2023

Computer Graphics Forum

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Image stylization has seen significant advancement and widespread interest over the years, leading to the development of a multitude of techniques. Extending these stylization techniques, such as Neural Style Transfer (NST), to videos is often achieved by applying them on a per‐frame basis. However, per‐frame stylization usually lacks temporal consistency, expressed by undesirable flickering artifacts. Most of the existing approaches for enforcing temporal consistency suffer from one or more of the following drawbacks: They (1) are only suitable for a limited range of techniques, (2) do not support online processing as they require the complete video as input, (3) cannot provide consistency for the task of stylization, or (4) do not provide interactive consistency control. Domain‐agnostic techniques for temporal consistency aim to eradicate flickering completely but typically disregard aesthetic aspects. For stylization tasks, however, consistency control is an essential requirement as a certain amount of flickering adds to the artistic look and feel. Moreover, making this control interactive is paramount from a usability perspective. To achieve the above requirements, we propose an approach that stylizes video streams in real‐time at full HD resolutions while providing interactive consistency control. We develop a lite optical‐flow network that operates at 80 Frames per second (FPS) on desktop systems with sufficient accuracy. Further, we employ an adaptive combination of local and global consistency features and enable interactive selection between them. Objective and subjective evaluations demonstrate that our method is superior to state‐of‐the‐art video consistency approaches. maxreimann.github.io/stream‐consistency

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Section: Discussionmentioning

confidence: 76%

Section: Discussionmentioning

confidence: 85%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Interactive Control over Temporal Consistency while Stylizing Video Streams

Shekhar

Reimann

Hilscher

et al. 2023

Computer Graphics Forum

Self Cite

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“…Selain itu, smartphone menyediakan aplikasi untuk editing foto yang jumlahnya lebih banyak dibandingan dengan kamera digital. Aplikasi ini dapat digunakan untuk mengedit foto yang dihasilkan oleh kamera smartphone, salah satu teknik editing yang digunakan adalah aplikasi Canva [4].…”

Section: Pendahuluanunclassified

Pelatihan Pengeditan Konten Produk Dengan Menggunakan Canva Bagi Pelaku Usaha Ekonomi Kreatif Desa Pengkok Kabupaten Gunungkidul

Indrianingsih¹,

Pujiastuti²,

Kusumaningrum³

2023

SJPKM

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Wabah virus corona 19 telah membawa dampak yang besar dalam bidang ekonomi hingga ke pelosok desa di seluruh Indonesia, salah satunya Desa Pengkok Kecamatan Patuk Kabupaten Gunungkidul Propinsi Daerah Istimewa Yogyakarta. Bagi rakyat yang bekerja di sektor informal tentu sangat berat dampak yang dirasakannya. Beberapa yang memiliki kemampuan lebih dapat membuat produk dalam ruang lingkup ekonomi kreatif, bagi yang tidak butuh peningkatan sumber daya manusia sehingga dapat membuat produk. Produk yang dihasilkan tentu harus segera dipasarkan. Cara pemasaran menggunakan media sosial sangat efektif dan efisien bagi mereka. Hanya kemampuan dalam membuat konten yang mengisi media sosial tersebut perlu dtingkatkan melalui pendampingan pelatihan editing video menggunakan aplikasi canva yang dapat dengan mudah diunduh melalui smartphone yang dimilikinya. Para pelaku usaha ekonomi kreatif di Desa Pengkok Patuk Gunungkidul dapat mengetahui dan memahami editing konten produk menggunakan Canva. 71,67% pelaku usaha ekonomi kreatif di Desa Pengkok Patuk Gunungkidul dapat melakukan editing konten produk menggunakan Canva. Secara keseluruhan prosentase kepuasan peserta pelatihan editing konten produk menggunakan Canva sebesar 81,48%

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