234 citations · 603 across the 20 of their papers we have counts for
6 papers · 1 filter
Oriented Object Detection with Transformer
Teli Ma, Mingyuan Mao, Honghui Zheng +6
Object detection with Transformers (DETR) has achieved a competitive performance over traditional detectors, such as Faster R-CNN. However, the potential of DETR remains largely un…
Probabilistic Ranking-Aware Ensembles for Enhanced Object Detections
Mingyuan Mao, Baochang Zhang, David Doermann +5
Model ensembles are becoming one of the most effective approaches for improving object detection performance already optimized for a single detector. Conventional methods directly…
Dual-stream Network for Visual Recognition
Mingyuan Mao, Renrui Zhang, Honghui Zheng +6
Transformers with remarkable global representation capacities achieve competitive results for visual tasks, but fail to consider high-level local pattern information in input image…
PAFNet: An Efficient Anchor-Free Object Detector Guidance
Ying Xin, Guanzhong Wang, Mingyuan Mao +5
Object detection is a basic but challenging task in computer vision, which plays a key role in a variety of industrial applications. However, object detectors based on deep learnin…
PP-YOLOv2: A Practical Object Detector
Xin Huang, Xinxin Wang, Wenyu Lv +10
Being effective and efficient is essential to an object detector for practical use. To meet these two concerns, we comprehensively evaluate a collection of existing refinements to…
Student-Teacher Feature Pyramid Matching for Anomaly Detection
Guodong Wang, Shumin Han, Errui Ding +1
Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies. This paper proposes a simple yet powerful appro…