262 citations · 532 across the 31 of their papers we have counts for
7 papers · 1 filter
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture
Jiansen Guo, Hong-Yu Zhou, Liansheng Wang +1
Recent medical image segmentation models are mostly hybrid, which integrate self-attention and convolution layers into the non-isomorphic architecture. However, one potential drawb…
A Survey on Graph Neural Networks and Graph Transformers in Computer Vision: A Task-Oriented Perspective
Chaoqi Chen, Yushuang Wu, Qiyuan Dai +5
Graph Neural Networks (GNNs) have gained momentum in graph representation learning and boosted the state of the art in a variety of areas, such as data mining (\emph{e.g.,} social…
ProCo: Prototype-aware Contrastive Learning for Long-tailed Medical Image Classification
Zhixiong Yang, Junwen Pan, Yanzhan Yang +4
Medical image classification has been widely adopted in medical image analysis. However, due to the difficulty of collecting and labeling data in the medical area, medical image da…
PieTrack: An MOT solution based on synthetic data training and self-supervised domain adaptation
Yirui Wang, Shenghua He, Youbao Tang +8
In order to cope with the increasing demand for labeling data and privacy issues with human detection, synthetic data has been used as a substitute and showing promising results in…
Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection
Chaoqi Chen, Jiongcheng Li, Hong-Yu Zhou +4
Domain Adaptive Object Detection (DAOD) focuses on improving the generalization ability of object detectors via knowledge transfer. Recent advances in DAOD strive to change the emp…
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
Yangji He, Weihan Liang, Dongyang Zhao +4
This paper presents new hierarchically cascaded transformers that can improve data efficiency through attribute surrogates learning and spectral tokens pooling. Vision transformers…