A color sketch creates a vivid depiction of a scene using sparse pencil strokes and casual colored brush strokes. The interactive drawing system ColorSketch can help novice users generate color sketches from photos. To preserve artistic freedom and expressiveness, the proposed system gives users full control over pencil strokes, while automatically augmenting pencil sketches using color mapping, brush stroke rendering, and blank area creation. Experimental and user study results demonstrate that users, especially novices, can create better color sketches with our system than when using traditional manual tools.
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http://dx.doi.org/10.1109/MCG.2016.37 | DOI Listing |
Sci Rep
January 2025
School of Software, Pingdingshan University, Pingdingshan, 467000, China.
In traditional Chinese painting, the genre of landscapes is unique and universally valued. For an untrained person to achieve such results is very difficult, requiring mastery of such things as brushwork, composition, and color. In this paper, we propose HA-GAN to transform sketches into Chinese landscape paintings, a new GAN-based framework that builds upon a hybrid attention generator and a discriminator.
View Article and Find Full Text PDFNatl Med J India
October 2024
Department of Anatomy, Dr DY Patil Medical College, Sector 5 Nerul, Navi Mumbai 400706, Maharashtra, India.
Background The challenge faced by an undergraduate medical student to draw factually correct histology diagrams needs to be addressed by the use of innovative teaching strategies. We introduced a new method to teach drawing of histology diagrams and compared its outcome with two preexisting methods. We obtained feedback from the students and faculty.
View Article and Find Full Text PDFSci Rep
October 2024
Art School, Northwest University, Xi'an, 710127, China.
Ancient murals embody profound historical, cultural, scientific, and artistic values, yet many are afflicted with challenges such as pigment shedding or missing parts. While deep learning-based completion techniques have yielded remarkable results in restoring natural images, their application to damaged murals has been unsatisfactory due to data shifts and limited modeling efficacy. This paper proposes a novel progressive reasoning network designed specifically for mural image completion, inspired by the mural painting process.
View Article and Find Full Text PDFPLoS One
September 2024
Department of Computer Science and Technology, Xinzhou Normal University, Xinzhou, China.
The current mainstream image restoration methods have difficulty fully learning the structure and color information of murals in mural image restoration tasks due to the limited size of the available datasets, resulting in problems such as structural loss and texture errors. This study proposes a two-stage mural restoration network based on an edge-constrained attention mechanism. This paper introduces additional sketches as inputs during the coarse restoration phase and incorporates a local edge loss function to enable the network to generate corresponding structural information based on the sketches.
View Article and Find Full Text PDFIEEE Trans Pattern Anal Mach Intell
December 2024
Applying diffusion models to image-to-image translation (I2I) has recently received increasing attention due to its practical applications. Previous attempts inject information from the source image into each denoising step for an iterative refinement, thus resulting in a time-consuming implementation. We propose an efficient method that equips a diffusion model with a lightweight translator, dubbed a Diffusion Model Translator (DMT), to accomplish I2I.
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