84 citations · 587 across the 66 of their papers we have counts for
8 papers · 1 filter
Self-supervised Tumor Segmentation through Layer Decomposition
Xiaoman Zhang, Weidi Xie, Chaoqin Huang +4
In this paper, we target self-supervised representation learning for zero-shot tumor segmentation. We make the following contributions: First, we advocate a zero-shot setting, wher…
Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction
Maosen Li, Siheng Chen, Yangheng Zhao +3
We propose a multiscale spatio-temporal graph neural network (MST-GNN) to predict the future 3D skeleton-based human poses in an action-category-agnostic manner. The core of MST-GN…
CaT: Weakly Supervised Object Detection with Category Transfer
Tianyue Cao, Lianyu Du, Xiaoyun Zhang +3
A large gap exists between fully-supervised object detection and weakly-supervised object detection. To narrow this gap, some methods consider knowledge transfer from additional fu…
Cooperative Learning for Noisy Supervision
Hao Wu, Jiangchao Yao, Ya Zhang +1
Learning with noisy labels has gained the enormous interest in the robust deep learning area. Recent studies have empirically disclosed that utilizing dual networks can enhance the…
MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets
Shixiang Feng, Yuhang Zhou, Xiaoman Zhang +2
Annotating multiple organs in 3D medical images is time-consuming and costly. Meanwhile, there exist many single-organ datasets with one specific organ annotated. This paper invest…
A Fourier-based Framework for Domain Generalization
Qinwei Xu, Ruipeng Zhang, Ya Zhang +2
Modern deep neural networks suffer from performance degradation when evaluated on testing data under different distributions from training data. Domain generalization aims at tackl…