An End-to-end Dynamic Point Cloud Geometry Compression in Latent Space (2023)
Journal Article
Jiang, Z., Wang, G., Tam, G. K. L., Song, C., Yang, B., & Li, F. W. B. (in press). An End-to-end Dynamic Point Cloud Geometry Compression in Latent Space. Displays, https://doi.org/10.1016/j.displa.2023.102528

Dynamic point clouds are widely used for 3D data representation in various applications such as immersive and mixed reality, robotics and autonomous driving. However, their irregularity and large scale make efficient compression and transmission a ch... Read More about An End-to-end Dynamic Point Cloud Geometry Compression in Latent Space.

A Differential Diffusion Theory for Participating Media (2023)
Journal Article
Cen, Y., Li, C., Li, F. W. B., Yang, B., & Liang, X. (in press). A Differential Diffusion Theory for Participating Media. Computer Graphics Forum, 42(7),

We present a novel approach to differentiable rendering for participating media, addressing the challenge of computing scene parameter derivatives. While existing methods focus on derivative computation within volumetric path tracing, they fail to si... Read More about A Differential Diffusion Theory for Participating Media.

WDFSR: Normalizing Flow based on Wavelet-Domain for Super-Resolution (2023)
Journal Article
Song, C., Li, S., Li, F. W. B., & Yang, B. (in press). WDFSR: Normalizing Flow based on Wavelet-Domain for Super-Resolution. Computational Visual Media,

We propose a Normalizing flow based on the wavelet framework for super-resolution called WDFSR. It learns the conditional distribution mapping between low-resolution images in the RGB domain and high-resolution images in the wavelet domain to generat... Read More about WDFSR: Normalizing Flow based on Wavelet-Domain for Super-Resolution.

C2SPoint: A classification-to-saliency network for point cloud saliency detection (2023)
Journal Article
Jiang, Z., Ding, L., Tam, G., Song, C., Li, F. W., & Yang, B. (in press). C2SPoint: A classification-to-saliency network for point cloud saliency detection. Computers and Graphics, https://doi.org/10.1016/j.cag.2023.07.003

Point cloud saliency detection is an important technique that support downstream tasks in 3D graphics and vision, like 3D model simplification, compression, reconstruction and viewpoint selection. Existing approaches often rely on hand-crafted featur... Read More about C2SPoint: A classification-to-saliency network for point cloud saliency detection.

IAACS: Image Aesthetic Assessment Through Color Composition And Space Formation (2023)
Journal Article
Yang, B., zhu, C., Li, F. W., Wei, T., Liang, X., & Wang, Q. (2023). IAACS: Image Aesthetic Assessment Through Color Composition And Space Formation. Virtual Reality & Intelligent Hardware, 5(1), https://doi.org/10.1016/j.vrih.2022.06.006

Judging how an image is visually appealing is a complicated and subjective task. This highly motivates having a machine learning model to automatically evaluate image aesthetic by matching the aesthetics of general public. Although deep learning meth... Read More about IAACS: Image Aesthetic Assessment Through Color Composition And Space Formation.

A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis (2023)
Journal Article
Zhou, K., Cai, R., Ma, Y., Tan, Q., Wang, X., Li, J., …Liang, X. (2023). A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis. IEEE Transactions on Visualization and Computer Graphics, 29(5), 2456-2466. https://doi.org/10.1109/tvcg.2023.3247092

As the most common idiopathic inflammatory myopathy in children, juvenile dermatomyositis (JDM) is characterized by skin rashes and muscle weakness. The childhood myositis assessment scale (CMAS) is commonly used to measure the degree of muscle invol... Read More about A Video-Based Augmented Reality System for Human-in-the-Loop Muscle Strength Assessment of Juvenile Dermatomyositis.

Distillation of human–object interaction contexts for action recognition (2022)
Journal Article
Almushyti, M., & Li, F. W. (2022). Distillation of human–object interaction contexts for action recognition. Computer Animation and Virtual Worlds, 33(5), Article e2107. https://doi.org/10.1002/cav.2107

Modeling spatial-temporal relations is imperative for recognizing human actions, especially when a human is interacting with objects, while multiple objects appear around the human differently over time. Most existing action recognition models focus... Read More about Distillation of human–object interaction contexts for action recognition.

Facial reshaping operator for controllable face beautification (2020)
Journal Article
Hu, S., Shum, H. P., Liang, X., Li, F. W., & Aslam, N. (2021). Facial reshaping operator for controllable face beautification. Expert Systems with Applications, 167, Article 114067. https://doi.org/10.1016/j.eswa.2020.114067

Posting attractive facial photos is part of everyday life in the social media era. Motivated by the demand, we propose a lightweight method to automatically and efficiently beautify the shapes of both portrait and non-portrait faces in photos, while... Read More about Facial reshaping operator for controllable face beautification.

Target‐driven cloud evolution using position‐based fluids (2020)
Journal Article
Zhang, Z., Li, Y., Yang, B., Li, F. W., & Liang, X. (2020). Target‐driven cloud evolution using position‐based fluids. Computer Animation and Virtual Worlds, 31(6), https://doi.org/10.1002/cav.1937

To effectively control particle‐based cloud evolution without imposing strict position constraints, we propose a novel method integrating a control force field and a phase transition control into the position‐based fluids (PBF) framework. To produce... Read More about Target‐driven cloud evolution using position‐based fluids.

Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network (2020)
Journal Article
Zhang, Z., Ma, Y., Li, Y., Li, F. W., Shum, H. P., Yang, B., …Liang, X. (2020). Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network. Graphical Models, 111, Article 101083. https://doi.org/10.1016/j.gmod.2020.101083

Physically-based cloud simulation is an effective approach for synthesizing realistic cloud. However, generating clouds with desired shapes requires a time-consuming process for selecting the appropriate simulation parameters. This paper addresses su... Read More about Cumuliform Cloud Formation Control using Parameter-Predicting Convolutional Neural Network.