562 citations · 1.7k across the 17 of their papers we have counts for
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3 papers · 1 filter
cs.CV2017★ 21 cited
Repulsion Loss: Detecting Pedestrians in a Crowd
Xinlong Wang, Tete Xiao, Yuning Jiang +3
Detecting individual pedestrians in a crowd remains a challenging problem since the pedestrians often gather together and occlude each other in real-world scenarios. In this paper,…
cs.CV2017★ 28 cited
MegDet: A Large Mini-Batch Object Detector
Chao Peng, Tete Xiao, Zeming Li +5
The improvements in recent CNN-based object detection works, from R-CNN [11], Fast/Faster R-CNN [10, 31] to recent Mask R-CNN [14] and RetinaNet [24], mainly come from new network,…
cs.CV2017★ 1 cited
What Can Help Pedestrian Detection?
Jiayuan Mao, Tete Xiao, Yuning Jiang +1
Aggregating extra features has been considered as an effective approach to boost traditional pedestrian detection methods. However, there is still a lack of studies on whether and…