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Volume 6 No. 2
05 June 2020

Yun-Peng Xiao, Yu-Kun Lai, Fang-Lue Zhang, Chunpeng Li, Lin Gao

2020, 6(2): 113-133.   doi:10.1007/s41095-020-0174-8
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Researchers have achieved great success in dealing with 2D images using deep learning. In recent years, 3D computer vision and geometry deep learning have gained ever more attention. Many advanced techniques for 3D shapes have been proposed for different applications. Unlike 2D images, which can be uniformly represented by a regular grid of pixels, 3D shapes have various representations, such as depth images, multi-view images, voxels, point clouds, meshes, implicit surfaces, etc. The perform...

Chao Zhang, Xuequan Lu, Katsuya Hotta, Xi Yang

2020, 6(2): 135-145.   doi:10.1007/s41095-020-0166-8
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In this paper we address the problem ofgeometric multi-model fitting using a few weakly annotated data points, which has been little studied so far. In weak annotating (WA), most manual annotations are supposed to be correct yet inevitably mixed with incorrect ones. Such WA data can naturally arise through interaction in various tasks. For example, in the case of homography estimation, one can easily annotate points on the same plane or object with a single label by observing the image. Motiv...

Miaopeng Li, Zimeng Zhou, Xinguo Liu

2020, 6(2): 147-156.   doi:10.1007/s41095-020-0171-y
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We present a multiview method for markerless motion capture of multiple people. The main challenge in this problem is to determine cross-view correspondences for the 2D joints in the presence of noise. We propose a 3D hypothesis clusteringtechnique to solve this problem. The core idea is to transform joint matching in 2D space into a clustering problem in a 3D hypothesis space. In this way, evidence from photometric appearance, multiview geometry, and bone length can be integrated to solve th...

Weiheng Lin, Beibei Wang, Lu Wang, Nicolas Holzschuch

2020, 6(2): 157-168.   doi:10.1007/s41095-020-0167-7
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Monte Carlo based methods such as path tracing are widely used in movie production. To achieve low noise, they require many samples per pixel, resulting in long rendering time. To reduce the cost, one solution is Monte Carlo denoising, which renders the image with fewer samples per pixel (as little as 128) and then denoises the resulting image. Many Monte Carlo denoising methods rely on deep learning: they use convolutional neural networks to learn the relationship between noisy images and re...

Jinjiang Li, Xiaomei Feng, Hui Fan

2020, 6(2): 169-189.   doi:10.1007/s41095-020-0172-x
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Improper functioning, or lack, of human cone cells leads to vision defects, making it impossible for affected persons to distinguish certain colors. Colorblind persons have color perception, but their ability to capture color information differs from that of normal people: colorblind and normal people perceive the same image differently. It is necessary to devise solutions to help persons with color blindness understand images and distinguish different colors. Most research on this subject is...

Ruochen Fan, Ming-Ming Cheng, Qibin Hou, Tai-Jiang Mu, Jingdong Wang, Shi-Min Hu

2020, 6(2): 191-204.   doi:10.1007/s41095-020-0173-9
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In this paper, we consider salient instance segmentation. As well as producing bounding boxes, our network also outputs high-quality instance-level segments as initial selections to indicate the regions of interest. Taking into account the category-independent property of each target, we design a single stage salient instance segmentation framework, with a novel segmentation branch. Our new branch regards not only local context inside each detection window but also the surrounding context, en...

Naoyuki Awano, Yuki Hayashi

2020, 6(2): 205-214.   doi:10.1007/s41095-020-0169-5
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Quantitatively evaluating the psychological and perceptual effects of objects is an important issue, but is difficult. In cognitive studies, the psychologicalpotential field (PPF), which represents psychological intensities in vision and can be calculated by applying computational algorithms to digital images, may help with this issue. Although studies have reported using the PPF to evaluate psychological effects, such as impressions, detailed investigations on how the PPF represents psycholo...

Xian Wu, Xiao-Nan Fang, Tao Chen, Fang-Lue Zhang

2020, 6(2): 215-224.   doi:10.1007/s41095-020-0168-6
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We propose a novel end-to-end deep learning framework, the Joint Matting Network (JMNet), to automatically generate alpha mattes for human images. We utilize the intrinsic structures of the human body as seen in images by introducing a pose estimation module, which can provide both global structural guidance and a local attention focus for the matting task. Our network model includes a pose network, a trimap network, a matting network, and a shared encoder to extract features for the above th...