10 citations · 35 across the 31 of their papers we have counts for
6 papers · 1 filter
MoEC: Mixture of Experts Implicit Neural Compression
Jianchen Zhao, Cheng-Ching Tseng, Ming Lu +4
Emerging Implicit Neural Representation (INR) is a promising data compression technique, which represents the data using the parameters of a Deep Neural Network (DNN). Existing met…
DiffusionTalker: Personalization and Acceleration for Speech-Driven 3D Face Diffuser
Peng Chen, Xiaobao Wei, Ming Lu +4
Speech-driven 3D facial animation has been an attractive task in both academia and industry. Traditional methods mostly focus on learning a deterministic mapping from speech to ani…
I-MedSAM: Implicit Medical Image Segmentation with Segment Anything
Xiaobao Wei, Jiajun Cao, Yizhu Jin +3
With the development of Deep Neural Networks (DNNs), many efforts have been made to handle medical image segmentation. Traditional methods such as nnUNet train specific segmentatio…
NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
Xiaobao Wei, Renrui Zhang, Jiarui Wu +4
Neural 3D reconstruction from multi-view images has recently attracted increasing attention from the community. Existing methods normally learn a neural field for the whole scene,…
Open-Vocabulary Point-Cloud Object Detection without 3D Annotation
Yuheng Lu, Chenfeng Xu, Xiaobao Wei +4
The goal of open-vocabulary detection is to identify novel objects based on arbitrary textual descriptions. In this paper, we address open-vocabulary 3D point-cloud detection by a…
WM-MoE: Weather-aware Multi-scale Mixture-of-Experts for Blind Adverse Weather Removal
Yulin Luo, Rui Zhao, Xiaobao Wei +7
Adverse weather removal tasks like deraining, desnowing, and dehazing are usually treated as separate tasks. However, in practical autonomous driving scenarios, the type, intensity…