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researcher

O. Yoshie

12 papers hereh-index 181.6k citations107 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author8

Across the 10 of 12 papers where every author was matched, so the position is known.

fields
  • cs.CV11
  • cs.AI1
same name
  • O. Yoshie — 2 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedPP-YOLOv2: A Practical Object Detector

93 citations · 149 across the 12 of their papers we have counts for

collaborators
Showing 2020Show all

4 papers · 1 filter

cs.CV2020

ExchNet: A Unified Hashing Network for Large-Scale Fine-Grained Image Retrieval

Quan Cui, Qing-Yuan Jiang, Xiu-Shen Wei +2

Retrieving content relevant images from a large-scale fine-grained dataset could suffer from intolerably slow query speed and highly redundant storage cost, due to high-dimensional…

cs.CV2020

Delving into the Imbalance of Positive Proposals in Two-stage Object Detection

Zheng Ge, Zequn Jie, Xin Huang +2

Imbalance issue is a major yet unsolved bottleneck for the current object detection models. In this work, we observe two crucial yet never discussed imbalance issues. The first imb…

cs.CV2020★ 31 cited

NMS by Representative Region: Towards Crowded Pedestrian Detection by Proposal Pairing

Xin Huang, Zheng Ge, Zequn Jie +1

Although significant progress has been made in pedestrian detection recently, pedestrian detection in crowded scenes is still challenging. The heavy occlusion between pedestrians i…

cs.CV2020★ 6 cited

PS-RCNN: Detecting Secondary Human Instances in a Crowd via Primary Object Suppression

Zheng Ge, Zequn Jie, Xin Huang +2

Detecting human bodies in highly crowded scenes is a challenging problem. Two main reasons result in such a problem: 1). weak visual cues of heavily occluded instances can hardly p…

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