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.

Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model (2023)
Conference Proceeding
Wang, Y., Leng, Z., Li, F. W. B., Wu, S., & Liang, X. (in press). Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model.

Text-driven human motion generation in computer vision is both significant and challenging. However, current methods are limited to producing either deterministic or imprecise motion sequences, failing to effectively control the temporal and spatial... Read More about Fg-T2M: Fine-Grained Text-Driven Human Motion Generation via Diffusion Model.

HSE: Hybrid Species Embedding for Deep Metric Learning (2023)
Conference Proceeding
Yang, B., Sun, H., Li, F. W. B., Chen, Z., Cai, J., & Song, C. (in press). HSE: Hybrid Species Embedding for Deep Metric Learning.

Deep metric learning is crucial for finding an embedding function that can generalize to training and testing data, including unknown test classes. However, limited training samples restrict the model's generalization to downstream tasks. While addin... Read More about HSE: Hybrid Species Embedding for Deep Metric Learning.

A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments (2023)
Conference Proceeding
Zhou, K., Chen, C., Ma, Y., Leng, Z., Shum, H. P., Li, F. W., & Liang, X. (in press). A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments. In Proceedings of the 2023 International Symposium on Mixed and Augmented Reality

As human exploration of space continues to progress, the use of Mixed Reality (MR) for simulating microgravity environments and facilitating training in hand-object interaction holds immense practical significance. However, hand-object interaction in... Read More about A Mixed Reality Training System for Hand-Object Interaction in Simulated Microgravity Environments.

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.

DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method (2023)
Conference Proceeding
Yang, B., Chen, Z., Li, F. W. B., Sun, H., & Cai, J. (in press). DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method.

We present a novel approach for modeling artists' drawing processes using an architecture that combines an unconditional generative adversarial network (GAN) with a multi-view generator and multi-discriminator. Our method excels in synthesizing vario... Read More about DrawGAN: Multi-view Generative Model Inspired By The Artist's Drawing Method.

Gamifying Experiential Learning Theory (2023)
Conference Proceeding
Alsaqqaf, A., & Li, F. W. (in press). Gamifying Experiential Learning Theory. In ICWL 2022, SETE 2022: Learning Technologies and Systems (16-28). https://doi.org/10.1007/978-3-031-33023-0_2

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.