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H. Qi

21 papers hereh-index 2710.2k citations100 works total

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

author position
  • middle author20

Across the 20 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CV20
  • cs.CR1
same name
  • H. Qi — 249 papers, h 16
  • H. Qi — 213 papers, h 7
  • H. Qi — 201 papers, h 9
  • H. Qi — 150 papers, h 30
  • H. Qi — 68 papers, h 21
  • H. Qi — 54 papers

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
20152023
most citedCenterNet: Keypoint Triplets for Object Detection

168 citations · 631 across the 21 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CR2019★ 106 cited

Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics

Yuezun Li, Xin Yang, Pu Sun +2

AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information. The need to develop and evaluate Dee…

cs.CV2019★ 168 cited

CenterNet: Keypoint Triplets for Object Detection

Kaiwen Duan, Song Bai, Lingxi Xie +3

In object detection, keypoint-based approaches often suffer a large number of incorrect object bounding boxes, arguably due to the lack of an additional look into the cropped regio…

cs.CV2019★ 14 cited

Exposing GAN-synthesized Faces Using Landmark Locations

Xin Yang, Yuezun Li, Honggang Qi +1

Generative adversary networks (GANs) have recently led to highly realistic image synthesis results. In this work, we describe a new method to expose GAN-synthesized images using th…

cs.CV2019★ 100 cited

See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification

Tao Hu, Honggang Qi, Qingming Huang +1

Data augmentation is usually adopted to increase the amount of training data, prevent overfitting and improve the performance of deep models. However, in practice, random data augm…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.