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Zengchang Qin

25 papers hereh-index 303.8k citations162 works total

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

author position
  • middle author13
  • last author9

Across the 22 of 25 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.CL4
  • cs.LG2
  • cs.MM2
  • cs.SI2
  • cs.GT1
same name
  • Zengchang Qin — 4 papers, h 3
  • Zengchang Qin — 2 papers, h 2
  • Zengchang Qin — 2 papers, h 2
  • Zengchang Qin — 1 paper, h 1

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
20152026
most citedData Augmentation in Emotion Classification Using Generative Adversarial Networks

78 citations · 245 across the 24 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019

Multi-Level Network for High-Speed Multi-Person Pose Estimation

Ying Huang, Jiankai Zhuang, Zengchang Qin

In multi-person pose estimation, the left/right joint type discrimination is always a hard problem because of the similar appearance. Traditionally, we solve this problem by stacki…

cs.CV2019

FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition

Ying Huang, Bin Sun, Haipeng Kan +2

Human pose estimation has made significant advancement in recent years. However, the existing datasets are limited in their coverage of pose variety. In this paper, we introduce a…

cs.CV2019★ 8 cited

DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue

Xiaoze Jiang, Jing Yu, Zengchang Qin +4

Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue involves multiple questions which cover a broad range of vis…

cs.CV2019★ 16 cited

Structured Knowledge Distillation for Dense Prediction

Yifan Liu, Changyong Shun, Jingdong Wang +1

In this work, we consider transferring the structure information from large networks to compact ones for dense prediction tasks in computer vision. Previous knowledge distillation…

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