6 citations · 15 across the 9 of their papers we have counts for
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cs.CV2023★ 2 cited
USD: Unknown Sensitive Detector Empowered by Decoupled Objectness and Segment Anything Model
Yulin He, Wei Chen, Yusong Tan +1
Open World Object Detection (OWOD) is a novel and challenging computer vision task that enables object detection with the ability to detect unknown objects. Existing methods typica…
cs.CL2023★ 2 cited
Improving Knowledge Graph Entity Alignment with Graph Augmentation
Feng Xie, Xiang Zeng, Bin Zhou +1
Entity alignment (EA) which links equivalent entities across different knowledge graphs (KGs) plays a crucial role in knowledge fusion. In recent years, graph neural networks (GNNs…
cs.CV2023★ 2 cited
Pseudo-label Correction and Learning For Semi-Supervised Object Detection
Yulin He, Wei Chen, Ke Liang +3
Pseudo-Labeling has emerged as a simple yet effective technique for semi-supervised object detection (SSOD). However, the inevitable noise problem in pseudo-labels significantly de…