27 citations · 80 across the 18 of their papers we have counts for
7 papers · 1 filter
DI-Net : Decomposed Implicit Garment Transfer Network for Digital Clothed 3D Human
Xiaojing Zhong, Yukun Su, Zhonghua Wu +2
3D virtual try-on enjoys many potential applications and hence has attracted wide attention. However, it remains a challenging task that has not been adequately solved. Existing 2D…
SARA: Controllable Makeup Transfer with Spatial Alignment and Region-Adaptive Normalization
Xiaojing Zhong, Xinyi Huang, Zhonghua Wu +2
Makeup transfer is a process of transferring the makeup style from a reference image to the source images, while preserving the source images' identities. This technique is highly…
LCReg: Long-Tailed Image Classification with Latent Categories based Recognition
Weide Liu, Zhonghua Wu, Yiming Wang +4
In this work, we tackle the challenging problem of long-tailed image recognition. Previous long-tailed recognition approaches mainly focus on data augmentation or re-balancing stra…
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation
Yicheng Wu, Zhonghua Wu, Hengcan Shi +3
New lesion segmentation is essential to estimate the disease progression and therapeutic effects during multiple sclerosis (MS) clinical treatments. However, the expensive data acq…
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation
Weide Liu, Zhonghua Wu, Yang Zhao +4
Current methods for few-shot segmentation (FSSeg) have mainly focused on improving the performance of novel classes while neglecting the performance of base classes. To overcome th…
Modeling Continuous Motion for 3D Point Cloud Object Tracking
Zhipeng Luo, Gongjie Zhang, Changqing Zhou +4
The task of 3D single object tracking (SOT) with LiDAR point clouds is crucial for various applications, such as autonomous driving and robotics. However, existing approaches have…
Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation
Zhonghua Wu, Yicheng Wu, Guosheng Lin +1
Weakly-supervised point cloud segmentation with extremely limited labels is highly desirable to alleviate the expensive costs of collecting densely annotated 3D points. This paper…