20 citations · 51 across the 13 of their papers we have counts for
17 papers
Accelerating DETR Convergence via Semantic-Aligned Matching
Gongjie Zhang, Zhipeng Luo, Yingchen Yu +2
The recently developed DEtection TRansformer (DETR) establishes a new object detection paradigm by eliminating a series of hand-crafted components. However, DETR suffers from extre…
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019
Zhengying Liu, Adrien Pavao, Zhen Xu +22
This paper reports the results and post-challenge analyses of ChaLearn's AutoDL challenge series, which helped sorting out a profusion of AutoML solutions for Deep Learning (DL) th…
MapRE: An Effective Semantic Mapping Approach for Low-resource Relation Extraction
Manqing Dong, Chunguang Pan, Zhipeng Luo
Neural relation extraction models have shown promising results in recent years; however, the model performance drops dramatically given only a few training samples. Recent works tr…
Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency
Zhipeng Luo, Zhongang Cai, Changqing Zhou +7
Deep learning-based 3D object detection has achieved unprecedented success with the advent of large-scale autonomous driving datasets. However, drastic performance degradation rema…
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Dawei Du, Longyin Wen, Pengfei Zhu +52
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.…
Domain Consistency Regularization for Unsupervised Multi-source Domain Adaptive Classification
Zhipeng Luo, Xiaobing Zhang, Shijian Lu +1
Deep learning-based multi-source unsupervised domain adaptation (MUDA) has been actively studied in recent years. Compared with single-source unsupervised domain adaptation (SUDA),…