Demo Data from VLDB 2026 / reviewers in the wild / expert
Wei Zeng 0019
dblp:80/1961-19
· DBLP profile ↗
8ranked-venue papers
0as first author
8since 2021 · last 2026
—ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 4 since 2021Graphics, computer vision, multimedia, augmented reality and games · 3 · 3 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 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
3 papers |
Geometric modeling and processing · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Geometric modeling and processing › computational geometry › containment queries
point inclusion |
1.0 | 1 | 2026 | An algorithm to compute the point inclusion of 2D planar shapes based on line segment substitution · Comput. Aided Des. 2026 |
Geometric modeling and processing › shape modeling › shape editing › mesh editing
mesh booleans |
0.9 | 1 | 2025 | Blending weight BSP Tree for mesh Boolean operations · Comput. Aided Des. 2025 |
Geometric modeling and processing › shape modeling › parametric modeling › spline surfaces
NURBS surface |
0.6 | 1 | 2022 | Area-Preserving Hierarchical NURBS Surfaces Computed by the Optimal Freeform Transformation · Comput. Aided Des. 2022 |
Geometric modeling and processing
solid modeling |
0.3 | 1 | 2025 | Blending weight BSP Tree for mesh Boolean operations · Comput. Aided Des. 2025 |
Methods — techniques the papers use, named apart from their topics
blending weight BSP tree · 0.9optimal freeform transformation · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | An algorithm to compute the point inclusion of 2D planar shapes based on line segment substitution
Kai Dai, Hangcheng Zhang, Yi-Jun Yang, Wei Zeng 0019 |
Comput. Aided Des. | 5 |
| 2025 | Blending weight BSP Tree for mesh Boolean operations
Hangcheng Zhang, Ganxuan Zhang, Kai Dai, Yi Liu 0103, Yi-Jun Yang, Wei Zeng 0019 |
Comput. Aided Des. | 8 |
| 2025 | Zero-shot image translation via query compensation and style enhancement
Yi-Jun Yang, Wei Zeng 0019 |
Eng. Appl. Artif. Intell. | 3 |
| 2025 | Multi-center brain age prediction via dual-modality fusion convolutional network
Xuebin Chang, Xiaoyan Jia, Simon B. Eickhoff, Debo Dong, Wei Zeng 0019 |
Medical Image Anal. | 5 |
| 2024 | Self-supervised multi-scale semantic consistency regularization for unsupervised image-to-image translation
Yi-Jun Yang, Wei Zeng 0019 |
Comput. Vis. Image Underst. | 3 |
| 2024 | Towards semantically continuous unpaired image-to-image translation via margin adaptive contrastive learning and wavelet transform
Yi-Jun Yang, Wei Zeng 0019 |
Expert Syst. Appl. | 3 |
| 2022 | Area-Preserving Hierarchical NURBS Surfaces Computed by the Optimal Freeform Transformation
Yi-Jun Yang, Wei Zeng 0019, Yu-Li Bi, Jin-Lan Xu, Gang Xu 0001, Xing-Jun Zhang |
Comput. Aided Des. | 3 |
| 2021 | Slice-sampling based 3D Object ClassificationabstractMultiview-based 3D object detection achieved great success in the past years. However, for some complex models with complex inner structures, the performances of these methods are not satisfactory. This paper provides a method based on slide sampling for 3D object classification. First, we slice and sample the model from the different depths and directions to get the model’s features. Then, a deep neural network designed based on the attention mechanism is used to classify the input data. The experiments show that the performance of our method is competitive on ModelNet. Moreover, for some special models with simple surfaces and complex inner structures, the performance of our method is outstanding and stable. Xiangwen Zhao, Yi-Jun Yang, Wei Zeng 0019, Liqun Yang |
ACML | 3 |