Demo Data from VLDB 2026 / reviewers in the wild / expert
Qionghua Wang
dblp:378/9425
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0002-8727-8843ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Rendering · 91% Virtual and augmented reality · 9% | |
| Network and information security
1 paper |
Cryptographic primitives and cryptanalysis · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Rendering › image-based rendering
light field display rendering |
0.9 | 1 | 2025 | Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025 |
Rendering › sampling
ray sampling |
0.9 | 1 | 2025 | Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025 |
Rendering
real-time rendering |
0.9 | 1 | 2025 | Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025 |
Cryptographic primitives and cryptanalysis › encryption
image encryption |
0.8 | 1 | 2024 | Non-Cascaded and Crosstalk-Free Multi-Image Encryption Based on Optical Scanning Holography Using 2D Orthogonal Compressive Sensing · IEEE Trans. Image Process. 2024 |
Cryptographic primitives and cryptanalysis › encryption › image encryption
optical encryption |
0.8 | 1 | 2024 | Non-Cascaded and Crosstalk-Free Multi-Image Encryption Based on Optical Scanning Holography Using 2D Orthogonal Compressive Sensing · IEEE Trans. Image Process. 2024 |
Virtual and augmented reality
3d display |
0.3 | 1 | 2025 | Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D Display · IEEE Trans. Vis. Comput. Graph. 2025 |
Methods — techniques the papers use, named apart from their topics
viewpoint mask texture · 0.9triangle culling · 0.9pixel culling · 0.9synthesis pupil encoding · 0.82d orthogonal compressive sensing · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Culling-Based Real-Time Rendering With Accurate Ray Sampling for High-Resolution Light Field 3D DisplayabstractReal-time rendering for light field displays (LFDs) enables human-computer three-dimensional (3D) interaction with smooth and realistic experience, which is potentially useful for 3D gaming, virtual reality, or surgical navigation. However, existing rendering methods realize a real-time rendering normally by sacrificing the 3D image resolution. We propose a culling-based real-time rendering (CBR) method with an accurate ray sampling, aimed at rendering the optimal synthetic images in real-time, which reproduce the high resolution 3D images. The synthetic image generation and display processes are first analyzed, identifying the condition of accurate ray sampling for generating the optimal synthetic images. Then the CBR method is proposed, significantly improving the generation speed of the optimal synthetic images under the accurate ray sampling condition by employing triangle culling in geometry shading stage and pixel culling using pre-computed viewpoint mask texture. Experiments show that accurate ray sampling generates the highest 3D image resolution, and the CBR method achieves superior frame rate, typically rendering 39.7 frames per second (fps) for a LFD with 4,225 viewpoints and a model of 16,301 triangle faces. Xiao-Shuai Hu, Xing-Yu Lin, Yi-Jian Liu, Min-Hao Xiang, Yu-Qiang Guo, Qionghua Wang |
IEEE Trans. Vis. Comput. Graph. | 7 |
| 2024 | Non-Cascaded and Crosstalk-Free Multi-Image Encryption Based on Optical Scanning Holography Using 2D Orthogonal Compressive SensingabstractWe propose a non-cascaded and crosstalk-free multi-image encryption method based on optical scanning holography and 2D orthogonal compressive sensing. This approach enables the simultaneous recording and encryption of multiple plaintext images without mechanical scanning, while allows for independent retrieval of each image with exceptional quality and no crosstalk. Two features would bring about more substantial security and privacy. The one is that, by employing a sequence of pre-designed structural patterns as encryption keys at the pupil, multiple samplings can be achieved and ultimately the holographic cyphertext can be obtained. These patterns are generated using a measurement matrix processed with the generalized orthogonal one. As a result, one can accomplish the differentiation of images prior to the recording and thus neither need to pretreat the pending images nor to suppress the out-of-focus noise in the decrypted image. The other one is that, the non-cascaded architecture ensures that different plaintexts do not share sub-keys. Meanwhile, compared to 1D orthogonal compressive sensing, the 2D counterpart makes the proposed method to synchronously deal with multiple images of more complexity, while acquire significantly high-quality decrypted images and far greater encryption capacity. Further, the regularities of conversion between 1D and 2D orthogonal compressive sensing are identified, which may be instructive when to manufacture a practical multi-image cryptosystem or a single-pixel imaging equipment. A more general method or concept named synthesis pupil encoding is advanced. It may provide an effective way to combine multiple encryption methods together into a non-cascaded one. Our method possesses nonlinearity and it is also promising in multi-image asymmetric or public key cryptosystem as well as multi-user multiplexing. Luozhi Zhang, Qionghua Wang, Xing Bai, Yuanyuan Wu 0001 |
IEEE Trans. Image Process. | 2 |