38 citations · 52 across the 7 of their papers we have counts for
7 papers · 1 filter
Beyond Bounding Box: Multimodal Knowledge Learning for Object Detection
Weixin Feng, Xingyuan Bu, Chenchen Zhang +1
Multimodal supervision has achieved promising results in many visual language understanding tasks, where the language plays an essential role as a hint or context for recognizing a…
GAIA: A Transfer Learning System of Object Detection that Fits Your Needs
Xingyuan Bu, Junran Peng, Junjie Yan +2
Transfer learning with pre-training on large-scale datasets has played an increasingly significant role in computer vision and natural language processing recently. However, as the…
DETR for Crowd Pedestrian Detection
Matthieu Lin, Chuming Li, Xingyuan Bu +5
Pedestrian detection in crowd scenes poses a challenging problem due to the heuristic defined mapping from anchors to pedestrians and the conflict between NMS and highly overlapped…
Large-Scale Object Detection in the Wild from Imbalanced Multi-Labels
Junran Peng, Xingyuan Bu, Ming Sun +3
Training with more data has always been the most stable and effective way of improving performance in deep learning era. As the largest object detection dataset so far, Open Images…
Learning an Efficient Network for Large-Scale Hierarchical Object Detection with Data Imbalance: 3rd Place Solution to Open Images Challenge 2019
Xingyuan Bu, Junran Peng, Changbao Wang +2
This report details our solution to the Google AI Open Images Challenge 2019 Object Detection Track. Based on our detailed analysis on the Open Images dataset, it is found that the…
Solution for Large-Scale Hierarchical Object Detection Datasets with Incomplete Annotation and Data Imbalance
Yuan Gao, Xingyuan Bu, Yang Hu +4
This report demonstrates our solution for the Open Images 2018 Challenge. Based on our detailed analysis on the Open Images Datasets (OID), it is found that there are four typical…