45 citations · 157 across the 24 of their papers we have counts for
6 papers · 1 filter
Mix and Reason: Reasoning over Semantic Topology with Data Mixing for Domain Generalization
Chaoqi Chen, Luyao Tang, Feng Liu +3
Domain generalization (DG) enables generalizing a learning machine from multiple seen source domains to an unseen target one. The general objective of DG methods is to learn semant…
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…
Towards Higher-order Topological Consistency for Unsupervised Network Alignment
Qingqiang Sun, Xuemin Lin, Ying Zhang +2
Network alignment task, which aims to identify corresponding nodes in different networks, is of great significance for many subsequent applications. Without the need for labeled an…
Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis
Gangming Zhao, Quanlong Feng, Chaoqi Chen +2
During clinical practice, radiologists often use attributes, e.g. morphological and appearance characteristics of a lesion, to aid disease diagnosis. Effectively modeling attribute…
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…
Compound Domain Generalization via Meta-Knowledge Encoding
Chaoqi Chen, Jiongcheng Li, Xiaoguang Han +2
Domain generalization (DG) aims to improve the generalization performance for an unseen target domain by using the knowledge of multiple seen source domains. Mainstream DG methods…