28 citations · 73 across the 16 of their papers we have counts for
28 papers
NeRFFaceEditing: Disentangled Face Editing in Neural Radiance Fields
Kaiwen Jiang, Shu-Yu Chen, Feng-Lin Liu +2
Recent methods for synthesizing 3D-aware face images have achieved rapid development thanks to neural radiance fields, allowing for high quality and fast inference speed. However,…
LiDAL: Inter-frame Uncertainty Based Active Learning for 3D LiDAR Semantic Segmentation
Zeyu Hu, Xuyang Bai, Runze Zhang +4
We propose LiDAL, a novel active learning method for 3D LiDAR semantic segmentation by exploiting inter-frame uncertainty among LiDAR frames. Our core idea is that a well-trained m…
MonoNeuralFusion: Online Monocular Neural 3D Reconstruction with Geometric Priors
Zi-Xin Zou, Shi-Sheng Huang, Yan-Pei Cao +3
High-fidelity 3D scene reconstruction from monocular videos continues to be challenging, especially for complete and fine-grained geometry reconstruction. The previous 3D reconstru…
DifferSketching: How Differently Do People Sketch 3D Objects?
Chufeng Xiao, Wanchao Su, Jing Liao +3
Multiple sketch datasets have been proposed to understand how people draw 3D objects. However, such datasets are often of small scale and cover a small set of objects or categories…
DeepPortraitDrawing: Generating Human Body Images from Freehand Sketches
Xian Wu, Chen Wang, Hongbo Fu +3
Researchers have explored various ways to generate realistic images from freehand sketches, e.g., for objects and human faces. However, how to generate realistic human body images…
NeuralHDHair: Automatic High-fidelity Hair Modeling from a Single Image Using Implicit Neural Representations
Keyu Wu, Yifan Ye, Lingchen Yang +3
Undoubtedly, high-fidelity 3D hair plays an indispensable role in digital humans. However, existing monocular hair modeling methods are either tricky to deploy in digital systems (…