Nerf-editing: geometry editing of neural radiance fields
Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great
potential in novel view synthesis of a scene. However, current NeRF-based methods cannot …
potential in novel view synthesis of a scene. However, current NeRF-based methods cannot …
Skeleton-free pose transfer for stylized 3d characters
We present the first method that automatically transfers poses between stylized 3D
characters without skeletal rigging. In contrast to previous attempts to learn pose …
characters without skeletal rigging. In contrast to previous attempts to learn pose …
Interactive nerf geometry editing with shape priors
Neural Radiance Fields (NeRFs) have shown great potential for tasks like novel view
synthesis of static 3D scenes. Since NeRFs are trained on a large number of input images, it …
synthesis of static 3D scenes. Since NeRFs are trained on a large number of input images, it …
MeshCLIP: Efficient cross-modal information processing for 3D mesh data in zero/few-shot learning
Y Song, N Liang, Q Guo, J Dai, J Bai, F He - Information Processing & …, 2023 - Elsevier
Abstract Text, 2D, and 3D information are crucial information representations in modern
science and management disciplines. However, complex and irregular 3D data produce …
science and management disciplines. However, complex and irregular 3D data produce …
A revisit of shape editing techniques: From the geometric to the neural viewpoint
Abstract 3D shape editing is widely used in a range of applications such as movie
production, computer games and computer aided design. It is also a popular research topic …
production, computer games and computer aided design. It is also a popular research topic …
TapMo: Shape-aware Motion Generation of Skeleton-free Characters
Previous motion generation methods are limited to the pre-rigged 3D human model,
hindering their applications in the animation of various non-rigged characters. In this work …
hindering their applications in the animation of various non-rigged characters. In this work …
Attwalk: Attentive cross-walks for deep mesh analysis
R Ben Izhak, A Lahav, A Tal - Proceedings of the IEEE/CVF …, 2022 - openaccess.thecvf.com
Mesh representation by random walks has been shown to benefit deep learning.
Randomness is indeed a powerful concept. However, it comes with a price--some walks …
Randomness is indeed a powerful concept. However, it comes with a price--some walks …
Lcollision: Fast generation of collision-free human poses using learned non-penetration constraints
We present LCollision, a learning-based method that synthesizes collision-free 3D human
poses. At the crux of our approach is a novel deep architecture that simultaneously decodes …
poses. At the crux of our approach is a novel deep architecture that simultaneously decodes …
Research on fraud detection method based on heterogeneous graph representation learning
X Zheng, C Feng, Z Yin, J Zhang, H Shen - Electronics, 2023 - mdpi.com
Detecting fraudulent users in social networks could reduce online fraud and
telecommunication fraud cases, which is essential to protect the lives and properties of …
telecommunication fraud cases, which is essential to protect the lives and properties of …
Unsupervised Representation Learning for Diverse Deformable Shape Collections
We introduce a novel learning-based method for encoding and manipulating 3D surface
meshes. Our method is specifically designed to create an interpretable embedding space for …
meshes. Our method is specifically designed to create an interpretable embedding space for …