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Item A Data-Driven Approach to Realistic Shape Morphing(The Eurographics Association and Blackwell Publishing Ltd., 2013) Gao, Lin; Lai, Yu-Kun; Huang, Qi-Xing; Hu, Shi-Min; I. Navazo, P. PoulinMorphing between 3D objects is a fundamental technique in computer graphics. Traditional methods of shape morphing focus on establishing meaningful correspondences and finding smooth interpolation between shapes. Such methods however only take geometric information as input and thus cannot in general avoid producing unnatural interpolation, in particular for large-scale deformations. This paper proposes a novel data-driven approach for shape morphing. Given a database with various models belonging to the same category, we treat them as data samples in the plausible deformation space. These models are then clustered to form local shape spaces of plausible deformations. We use a simple metric to reasonably represent the closeness between pairs of models. Given source and target models, the morphing problem is casted as a global optimization problem of finding a minimal distance path within the local shape spaces connecting these models. Under the guidance of intermediate models in the path, an extended as-rigid-as-possible interpolation is used to produce the final morphing. By exploiting the knowledge of plausible models, our approach produces realistic morphing for challenging cases as demonstrated by various examples in the paper.Item A Rigging-Skinning Scheme to Control Fluid Simulation(The Eurographics Association and John Wiley & Sons Ltd., 2019) Lu, Jia-Ming; Chen, Xiao-Song; Yan, Xiao; Li, Chen-Feng; Lin, Ming; Hu, Shi-Min; Lee, Jehee and Theobalt, Christian and Wetzstein, GordonInspired by skeletal animation, a novel rigging-skinning flow control scheme is proposed to animate fluids intuitively and efficiently. The new animation pipeline creates fluid animation via two steps: fluid rigging and fluid skinning. The fluid rig is defined by a point cloud with rigid-body movement and incompressible deformation, whose time series can be intuitively specified by a rigid body motion and a constrained free-form deformation, respectively. The fluid skin generates plausible fluid flows by virtually fluidizing the point-cloud fluid rig with adjustable zero- and first-order flow features and at fixed computational cost. Fluid rigging allows the animator to conveniently specify the desired low-frequency flow motion through intuitive manipulations of a point cloud, while fluid skinning truthfully and efficiently converts the motion specified on the fluid rig into plausible flows of the animation fluid, with adjustable fine-scale effects. Besides being intuitive, the rigging-skinning scheme for fluid animation is robust and highly efficient, avoiding completely iterative trials or time-consuming nonlinear optimization. It is also versatile, supporting both particle- and grid- based fluid solvers. A series of examples including liquid, gas and mixed scenes are presented to demonstrate the performance of the new animation pipeline.Item Learning Explicit Smoothing Kernels for Joint Image Filtering(The Eurographics Association and John Wiley & Sons Ltd., 2019) Fang, Xiaonan; Wang, Miao; Shamir, Ariel; Hu, Shi-Min; Lee, Jehee and Theobalt, Christian and Wetzstein, GordonSmoothing noises while preserving strong edges in images is an important problem in image processing. Image smoothing filters can be either explicit (based on local weighted average) or implicit (based on global optimization). Implicit methods are usually time-consuming and cannot be applied to joint image filtering tasks, i.e., leveraging the structural information of a guidance image to filter a target image.Previous deep learning based image smoothing filters are all implicit and unavailable for joint filtering. In this paper, we propose to learn explicit guidance feature maps as well as offset maps from the guidance image and smoothing parameter that can be utilized to smooth the input itself or to filter images in other target domains. We design a deep convolutional neural network consisting of a fully-convolution block for guidance and offset maps extraction together with a stacked spatially varying deformable convolution block for joint image filtering. Our models can approximate several representative image smoothing filters with high accuracy comparable to state-of-the-art methods, and serve as general tools for other joint image filtering tasks, such as color interpolation, depth map upsampling, saliency map upsampling, flash/non-flash image denoising and RGB/NIR image denoising.Item Interactive Image-Guided Modeling of Extruded Shapes(The Eurographics Association and John Wiley and Sons Ltd., 2014) Cao, Yan-Pei; Ju, Tao; Fu, Zhao; Hu, Shi-Min; J. Keyser, Y. J. Kim, and P. WonkaA recent trend in interactive modeling of 3D shapes from a single image is designing minimal interfaces, and accompanying algorithms, for modeling a specific class of objects. Expanding upon the range of shapes that existing minimal interfaces can model, we present an interactive image-guided tool for modeling shapes made up of extruded parts. An extruded part is represented by extruding a closed planar curve, called base, in the direction orthogonal to the base. To model each extruded part, the user only needs to sketch the projected base shape in the image. The main technical contribution is a novel optimization-based approach for recovering the 3D normal of the base of an extruded object by exploring both geometric regularity of the sketched curve and image contents. We developed a convenient interface for modeling multi-part shapes and a method for optimizing the relative placement of the parts. Our tool is validated using synthetic data and tested on real-world images.Item Data-Driven Object Manipulation in Images(The Eurographics Association and John Wiley and Sons Ltd., 2012) Goldberg, Chen; Chen, Tao; Zhang, Fang-Lue; Shamir, Ariel; Hu, Shi-Min; P. Cignoni and T. ErtlWe present a framework for interactively manipulating objects in a photograph using related objects obtained from internet images. Given an image, the user selects an object to modify, and provides keywords to describe it. Objects with a similar shape are retrieved and segmented from online images matching the keywords, and deformed to correspond with the selected object. By matching the candidate object and adjusting manipulation parameters, our method appropriately modifies candidate objects and composites them into the scene. Supported manipulations include transferring texture, color and shape from the matched object to the target in a seamless manner. We demonstrate the versatility of our framework using several inputs of varying complexity, for object completion, augmentation, replacement and revealing. Our results are evaluated using a user study.Item Saliency-aware Real-time Volumetric Fusion for Object Reconstruction(The Eurographics Association and John Wiley & Sons Ltd., 2016) Yang, Sheng; Chen, Kang; Liu, Minghua; Fu, Hongbo; Hu, Shi-Min; Jernej Barbic and Wen-Chieh Lin and Olga Sorkine-HornungWe present a real-time approach for acquiring 3D objects with high fidelity using hand-held consumer-level RGB-D scanning devices. Existing real-time reconstruction methods typically do not take the point of interest into account, and thus might fail to produce clean reconstruction results of desired objects due to distracting objects or backgrounds. In addition, any changes in background during scanning, which can often occur in real scenarios, can easily break up the whole reconstruction process. To address these issues, we incorporate visual saliency into a traditional real-time volumetric fusion pipeline. Salient regions detected from RGB-D frames suggest user-intended objects, and by understanding user intentions our approach can put more emphasis on important targets, and meanwhile, eliminate disturbance of non-important objects. Experimental results on realworld scans demonstrate that our system is capable of effectively acquiring geometric information of salient objects in cluttered real-world scenes, even if the backgrounds are changing.Item Appearance Harmonization for Single Image Shadow Removal(The Eurographics Association and John Wiley & Sons Ltd., 2016) Ma, Li-Qian; Wang, Jue; Shechtman, Eli; Sunkavalli, Kalyan; Hu, Shi-Min; Eitan Grinspun and Bernd Bickel and Yoshinori DobashiShadow removal is a challenging problem and previous approaches often produce de-shadowed regions that are visually inconsistent with the rest of the image. We propose an automatic shadow region harmonization approach that makes the appearance of a de-shadowed region (produced using any previous technique) compatible with the rest of the image. We use a shadow-guided patch-based image synthesis approach that reconstructs the shadow region using patches sampled from nonshadowed regions. This result is then refined based on the reconstruction confidence to handle unique textures. Qualitative comparisons over a wide range of images, and a quantitative evaluation on a benchmark dataset show that our technique significantly improves upon the state-of-the-art.Item A Shape-Preserving Approach to Image Resizing(The Eurographics Association and Blackwell Publishing Ltd, 2009) Zhang, Guo-Xin; Cheng, Ming-Ming; Hu, Shi-Min; Martin, Ralph R.We present a novel image resizing method which attempts to ensure that important local regions undergo a geometric similarity transformation, and at the same time, to preserve image edge structure. To accomplish this, we define handles to describe both local regions and image edges, and assign a weight for each handle based on an importance map for the source image. Inspired by conformal energy, which is widely used in geometry processing, we construct a novel quadratic distortion energy to measure the shape distortion for each handle. The resizing result is obtained by minimizing the weighted sum of the quadratic distortion energies of all handles. Compared to previous methods, our method allows distortion to be diffused better in all directions, and important image edges are well-preserved. The method is efficient, and offers a closed form solution.Item Deep Video Stabilization Using Adversarial Networks(The Eurographics Association and John Wiley & Sons Ltd., 2018) Xu, Sen-Zhe; Hu, Jun; Wang, Miao; Mu, Tai-Jiang; Hu, Shi-Min; Fu, Hongbo and Ghosh, Abhijeet and Kopf, JohannesVideo stabilization is necessary for many hand-held shot videos. In the past decades, although various video stabilization methods were proposed based on the smoothing of 2D, 2.5D or 3D camera paths, hardly have there been any deep learning methods to solve this problem. Instead of explicitly estimating and smoothing the camera path, we present a novel online deep learning framework to learn the stabilization transformation for each unsteady frame, given historical steady frames. Our network is composed of a generative network with spatial transformer networks embedded in different layers, and generates a stable frame for the incoming unstable frame by computing an appropriate affine transformation. We also introduce an adversarial network to determine the stability of a piece of video. The network is trained directly using the pair of steady and unsteady videos. Experiments show that our method can produce similar results as traditional methods, moreover, it is capable of handling challenging unsteady video of low quality, where traditional methods fail, such as video with heavy noise or multiple exposures. Our method runs in real time, which is much faster than traditional methods.Item Structure Aware Visual Cryptography(The Eurographics Association and John Wiley and Sons Ltd., 2014) Liu, Bin; Martin, Ralph R.; Huang, Ji-Wu; Hu, Shi-Min; J. Keyser, Y. J. Kim, and P. WonkaVisual cryptography is an encryption technique that hides a secret image by distributing it between some shared images made up of seemingly random black-and-white pixels. Extended visual cryptography (EVC) goes further in that the shared images instead represent meaningful binary pictures. The original approach to EVC suffered from low contrast, so later papers considered how to improve the visual quality of the results by enhancing contrast of the shared images. This work further improves the appearance of the shared images by preserving edge structures within them using a framework of dithering followed by a detail recovery operation.We are also careful to suppress noise in smooth areas.