Zobrazeno 1 - 10
of 343
pro vyhledávání: '"Rosin, P. L."'
Autor:
Tang, Yizhe, Wang, Yue, Hu, Teng, Yi, Ran, Tan, Xin, Ma, Lizhuang, Lai, Yu-Kun, Rosin, Paul L.
Stroke-based Rendering (SBR) aims to decompose an input image into a sequence of parameterized strokes, which can be rendered into a painting that resembles the input image. Recently, Neural Painting methods that utilize deep learning and reinforceme
Externí odkaz:
http://arxiv.org/abs/2410.16418
SVG (Scalable Vector Graphics) is a widely used graphics format that possesses excellent scalability and editability. Image vectorization, which aims to convert raster images to SVGs, is an important yet challenging problem in computer vision and gra
Externí odkaz:
http://arxiv.org/abs/2406.09794
In this paper, we propose Image Downscaling Assessment by Rate-Distortion (IDA-RD), a novel measure to quantitatively evaluate image downscaling algorithms. In contrast to image-based methods that measure the quality of downscaled images, ours is pro
Externí odkaz:
http://arxiv.org/abs/2403.15139
The advancement of knowledge distillation has played a crucial role in enabling the transfer of knowledge from larger teacher models to smaller and more efficient student models, and is particularly beneficial for online and resource-constrained appl
Externí odkaz:
http://arxiv.org/abs/2402.05305
Semi-supervised learning aims to help reduce the cost of the manual labelling process by leveraging valuable features extracted from a substantial pool of unlabeled data alongside a limited set of labelled data during the training phase. Since pixel-
Externí odkaz:
http://arxiv.org/abs/2311.13716
Vector graphics are widely used in graphical designs and have received more and more attention. However, unlike raster images which can be easily obtained, acquiring high-quality vector graphics, typically through automatically converting from raster
Externí odkaz:
http://arxiv.org/abs/2311.05276
Semi-supervised learning has been well developed to help reduce the cost of manual labelling by exploiting a large quantity of unlabelled data. Especially in the application of land cover classification, pixel-level manual labelling in large-scale im
Externí odkaz:
http://arxiv.org/abs/2305.10344
Image aesthetics assessment (IAA) is a challenging task due to its highly subjective nature. Most of the current studies rely on large-scale datasets (e.g., AVA and AADB) to learn a general model for all kinds of photography images. However, little l
Externí odkaz:
http://arxiv.org/abs/2303.15166
Universal domain adaptation (UniDA) aims to transfer the knowledge from a labeled source domain to an unlabeled target domain without any assumptions of the label sets, which requires distinguishing the unknown samples from the known ones in the targ
Externí odkaz:
http://arxiv.org/abs/2209.09616
Universal domain adaptation (UniDA) aims to transfer the knowledge of common classes from the source domain to the target domain without any prior knowledge on the label set, which requires distinguishing in the target domain the unknown samples from
Externí odkaz:
http://arxiv.org/abs/2207.09280