The Visual Computer: International Journal of Computer Graphics

Decorative plants require skillful pruning by gardeners. However, conventional plant modeling techniques have focused only on the biological growth rules of wild plants and do not yet consider artificial care. In this study, an interactive system ...

Semantic segmentation of point clouds, aiming to assign each point a semantic category, is critical to 3D scene understanding. Although significant advances in recent years, most of the existing methods still suffer from either the object-level ...

Personality and emotion as intrinsic factors often have great influences on the cognition of people’s behavior. In computer vision, there is a lot of work done on the recognition of emotions, such as classification of a person’s emotions via ...

Image smoothing is an important processing operation that highlights low-frequency structural parts of an image and suppresses the noise and high-frequency textures. In the paper, we post an intriguing question of how to combine the paired ...

We introduce a multimodal feature fusion network (MFFNet) for 3D point cloud semantic segmentation. Unlike previous methods that directly learn from colored point clouds (XYZRGB), MFFNet transforms point clouds to 2D RGB image and frequency image ...

Though a number of point cloud learning methods have been proposed to handle unordered points, most of them are supervised and require labels for training. By contrast, unsupervised learning of point cloud data has received much less attention to ...

The 6D (6 Degree of freedom) pose estimation (or pose measurement) of machined reflective texture-less objects, which are common in industry, is a significant but challenging technique. It has attracted increasing attention in academia and ...

Rock fractures are an important indicator for assessing the quality of rock masses. The significant differences in the color and texture distributions of rock mass exposures lead to great challenges in the automated extraction of fractures from ...

Image restoration is an inevitable pre-processing step in most satellite imaging applications. The satellite imaging modality such as Synthetic Aperture Radar (SAR) is prone to speckle distortions due to constructive and destructive interference ...

For the limitations of global feature-based deep learning point cloud registration algorithms in partial point cloud registration, this paper proposes a partial point cloud registration algorithm NcPE-PNLK combining global features and ...

There is a need for efficient methods to retrieve and obtain the visual data that a client need. New methods for content-based image retrieval (CBIR) have emerged due to recent developments in deep neural networks. However, there are still issues ...

Reflectance transformation imaging (RTI) is one of the most widely used techniques in order to digitize and analyze material appearance of a surface, finding a great level of utility and applicability in the field of cultural heritage as well as ...

Inexpensive cameras, different acquisition devices and mobile phones have resulted in the production of digital images in all spheres of life. There is common of these images for extracting useful information in many fields to perform image ...

Recently, the success of Transformer in natural language processing and image processing inspires researchers to apply Transformer in point cloud processing. However, existing point cloud Transformer methods have problems with massive parameters, ...

With the growth in utilizing desktop sharing and remote control applications in recent years for many purposes like online education and remote working, quality assessment (QA) of screen images has become a hot topic. It could be used to enhance ...

This paper investigates challenging fully unsupervised defogging problems, i.e., how to remove fog by feeding only foggy images in deep neural networks rather than using paired or unpaired synthetic images, and how to overcome the problems of ...

Addressing the intricate task of aircraft pose estimation in challenging airport environments, we introduce a dual attention module (DAM) inspired by the human visual system. Comprising two innovative sub-modules, the Inverse Parallel Multi-...$\mathrm{}$

Scene text image super-resolution (STISR) aims to enhance the resolution and visual quality of low-resolution scene text images, thereby improving the performance of some text-related downstream vision tasks. However, many existing STISR methods ...

To equip convolutional neural networks (CNNs) with explainability, it is essential to interpret how opaque models make specific decisions, understand what causes the errors, improve the architecture design, and identify unethical biases in the ...

6D object pose estimation is an important application of computer vision and a basic module in robotic manipulation, but dealing with occlusion in a cluttered environment, handling symmetries, and textureless surfaces, are real issues. Other ...

In this paper, we present DualMLP, a novel 3D model that introduces the idea of a two-stream network for existing 3D models to handle the trade-off between the number of points and the computational overhead. Existing works on point clouds use a ...

With the advent of generative adversarial networks (GAN), an astonishing advancement has been made in the generation of art painting in recent years. However, existing methods still suffer problems such as color confusion or blurred details. In ...$\mathrm{}\mathrm{}$

Decoupling the mixed face features to obtain identity features that are not disturbed by age information is the key to achieving cross-age face recognition. Established mainstream identity feature extraction methods decouple facial representations ...

Due to the complex underwater environment and the selective absorption and scattering effect of water on light waves, underwater images often suffer from issues such as low contrast, color distortion, and blurred details. This paper presents a ...

To improve the low accuracy problem of existing point cloud registration algorithms attributed to deficient point cloud geometric features, we proposed a new point cloud registration network inspired by dynamic feature extraction and the graph ...

An invisible layer of knowledge is progressively growing with the emergence of situated visualizations and reality-based information retrieval systems. In essence, digital content will overlap with real-world entities, eventually providing ...

In this paper, we aim to improve super-resolution (SR) imaging quality on 4K/8K images with a negligible increase in computational cost and alleviate the accuracy drop after quantization. Experiments have discovered two phenomena: (1) the re-...

Face recognition for surveillance remains a complex challenge due to the disparity between low-resolution (LR) face images captured by surveillance cameras and the typically high-resolution (HR) face images in databases. To address this cross-...

Nowadays, 3D human models are widely used in the garment industry where it is important to reconstruct compliant human model from scan of the body under partial dress for privacy reasons. A new 3D human construction method based on the combination ...

Recognizing cartoon characters accurately is important for animators to design and create cartoon scenarios by utilizing existing cartoon materials. Current deep learning approaches are sensitive to image rotation and heavily rely on rich textures ...