Browsing by Author "Zhang, Caiming"

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    Computer-assisted Relief Modelling: A Comprehensive Survey
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Zhang, Yu-Wei; Wu, Jing; Ji, Zhongping; Wei, Mingqiang; Zhang, Caiming; Giachetti, Andrea and Rushmeyer, Holly
    As an art form between drawing and sculpture, relief has been widely used in a variety of media for signs, narratives, decorations and other purposes. Traditional relief creation relies on both professional skills and artistic expertise, which is extremely timeconsuming. Recently, automatic or semi-automatic relief modelling from a 3D object or a 2D image has been a subject of interest in computer graphics. Various methods have been proposed to generate reliefs with few user interactions or minor human efforts, while preserving or enhancing the appearance of the input. This survey provides a comprehensive review of the advances in computer-assisted relief modelling during the past decade. First, we provide an overview of relief types and their art characteristics. Then, we introduce the key techniques of object-space methods and image-space methods respectively. Advantages and limitations of each category are discussed in details. We conclude the report by discussing directions for possible future research.
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    From 2.5D Bas‐relief to 3D Portrait Model
    (© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2020) Zhang, Yu‐Wei; Wang, Wenping; Chen, Yanzhao; Liu, Hui; Ji, Zhongping; Zhang, Caiming; Benes, Bedrich and Hauser, Helwig
    In contrast to 3D model that can be freely observed, p ortrait bas‐relief projects slightly from the background and is limited by fixed viewpoint. In this paper, we propose a novel method to reconstruct the underlying 3D shape from a single 2.5D bas‐relief, providing observers wider viewing perspectives. Our target is to make the reconstructed portrait has natural depth ordering and similar appearance to the input. To achieve this, we first use a 3D template face to fit the portrait. Then, we optimize the face shape by normal transfer and Poisson surface reconstruction. The hair and body regions are finally reconstructed and combined with the 3D face. From the resulting 3D shape, one can generate new reliefs with varying poses and thickness, freeing the input one from fixed view. A number of experimental results verify the effectiveness of our method.
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    Neural Modelling of Flower Bas‐relief from 2D Line Drawing
    (© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd, 2021) Zhang, Yu‐Wei; Wang, Jinlei; Wang, Wenping; Chen, Yanzhao; Liu, Hui; Ji, Zhongping; Zhang, Caiming; Benes, Bedrich and Hauser, Helwig
    Different from other types of bas‐reliefs, a flower bas‐relief contains a large number of depth‐discontinuity edges. Most existing line‐based methods reconstruct free‐form surfaces by ignoring the depth‐discontinuities, thus are less efficient in modeling flower bas‐reliefs. This paper presents a neural‐based solution which benefits from the recent advances in CNN. Specially, we use line gradients to encode the depth orderings at leaf edges. Given a line drawing, a heuristic method is first proposed to compute 2D gradients at lines. Line gradients and dense curvatures interpolated from sparse user inputs are then fed into a neural network, which outputs depths and normals of the final bas‐relief. In addition, we introduce an object‐based method to generate flower bas‐reliefs and line drawings for network training. Extensive experiments show that our method is effective in modelling bas‐reliefs with depth‐discontinuity edges. User evaluation also shows that our method is intuitive and accessible to common users.