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Mingliang Xu

7 papers hereh-index 11299 citations25 works total

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

author position
  • middle author6
  • last author1

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV7
same name
  • Mingliang Xu — 53 papers, h 49
  • Mingliang Xu — 9 papers, h 4
  • Mingliang Xu — 6 papers, h 15
  • Mingliang Xu — 6 papers, h 8
  • Mingliang Xu — 4 papers, h 7
  • Mingliang Xu — 2 papers, h 7

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
20212024
most citedOSIC: A New One-Stage Image Captioner Coined

2 citations · 3 across the 7 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CV2022

Long-Range Zero-Shot Generative Deep Network Quantization

Yan Luo, Yangcheng Gao, Zhao Zhang +3

Quantization approximates a deep network model with floating-point numbers by the one with low bit width numbers, in order to accelerate inference and reduce computation. Quantizin…

cs.CV2022

Seeing Through the Noisy Dark: Towards Real-world Low-Light Image Enhancement and Denoising

Jiahuan Ren, Zhao Zhang, Richang Hong +3

Low-light image enhancement (LLIE) aims at improving the illumination and visibility of dark images with lighting noise. To handle the real-world low-light images often with heavy…

cs.CV2022★ 2 cited

OSIC: A New One-Stage Image Captioner Coined

Bo Wang, Zhao Zhang, Mingbo Zhao +3

Mainstream image caption models are usually two-stage captioners, i.e., calculating object features by pre-trained detector, and feeding them into a language model to generate text…

cs.CV2022★ 1 cited

Bilaterally Slimmable Transformer for Elastic and Efficient Visual Question Answering

Zhou Yu, Zitian Jin, Jun Yu +3

Recent advances in Transformer architectures [1] have brought remarkable improvements to visual question answering (VQA). Nevertheless, Transformer-based VQA models are usually dee…

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