Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Dou, Yishun"'
Current Facial Action Unit (FAU) detection methods generally encounter difficulties due to the scarcity of labeled video training data and the limited number of training face IDs, which renders the trained feature extractor insufficient coverage for
Externí odkaz:
http://arxiv.org/abs/2407.11468
We propose a novel compact and efficient neural BRDF offering highly versatile material representation, yet with very-light memory and neural computation consumption towards achieving real-time rendering. The results in Figure 1, rendered at full HD
Externí odkaz:
http://arxiv.org/abs/2310.08332
Meshes are widely used in 3D computer vision and graphics, but their irregular topology poses challenges in applying them to existing neural network architectures. Recent advances in mesh neural networks turn to remeshing and push the boundary of pio
Externí odkaz:
http://arxiv.org/abs/2308.12530
Autor:
Li, Yuhan, Dou, Yishun, Shi, Yue, Lei, Yu, Chen, Xuanhong, Zhang, Yi, Zhou, Peng, Ni, Bingbing
While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation. In response, we introduce
Externí odkaz:
http://arxiv.org/abs/2308.10608
We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc. On one hand, to precisely capture local fine detailed
Externí odkaz:
http://arxiv.org/abs/2303.10406
People talk with diversified styles. For one piece of speech, different talking styles exhibit significant differences in the facial and head pose movements. For example, the "excited" style usually talks with the mouth wide open, while the "solemn"
Externí odkaz:
http://arxiv.org/abs/2111.00203