E
Enhua Wu
Researcher at Chinese Academy of Sciences
Publications - 289
Citations - 23216
Enhua Wu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Rendering (computer graphics) & Computer science. The author has an hindex of 24, co-authored 266 publications receiving 10340 citations. Previous affiliations of Enhua Wu include University of Macau & Academia Sinica.
Papers
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Proceedings Article
Training Binary Neural Networks through Learning with Noisy Supervision
TL;DR: Experimental results on benchmark datasets indicate that the proposed binarization technique attains consistent improvements over baselines.
Proceedings ArticleDOI
A particle-based method for viscoelastic fluids animation
TL;DR: Benefiting from the Lagrangian nature of Smoothed Particle Hydrodynamics, large flow deformation can be handled more easily and naturally and the melting and flowing phenomena, such as lava flow and wax melting, are achieved.
Proceedings ArticleDOI
Dynamic LOD on GPU
TL;DR: This paper presents a novel approach to implementing dynamic LOD on GPU based on seamless geometry image atlas, which is a 3D surface representation in parameter space by combining the features of geometry images and poly-cube maps.
Journal ArticleDOI
The Dual‐microfacet Model for Capturing Thin Transparent Slabs
Qiang Dai,Qiang Dai,Jiaping Wang,Yiming Liu,Yiming Liu,John Snyder,Enhua Wu,Enhua Wu,Baining Guo +8 more
TL;DR: This work presents a new model, called the dual‐microfacet, for those materials such as paper and plastic formed by a thin, transparent slab lying between two surfaces of spatially varying roughness, which captures both angular and spatial variation in the BTDF and provides a good match to measured materials.
Journal ArticleDOI
Technical Section: Point-in-polygon tests by convex decomposition
Jing Li,Wencheng Wang,Enhua Wu +2 more
TL;DR: The paper presents a new algorithm for point-in-polygon queries that can run much faster than the trapezoidation-based algorithms, up to over double folds in maximum.