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F. Wang

4 papers hereh-index 252.5k citations131 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV3
  • cs.IR1
same name
  • F. Wang — 56 papers, h 81
  • F. Wang — 47 papers
  • F. Wang — 41 papers
  • F. Wang — 35 papers
  • F. Wang — 28 papers
  • F. Wang — 20 papers, h 22

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

most citedUCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning

20 citations · 26 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 1 cited

SPCNet: Stepwise Point Cloud Completion Network

Fei Hu, Honghua Chen, Xuequan Lu +5

How will you repair a physical object with large missings? You may first recover its global yet coarse shape and stepwise increase its local details. We are motivated to imitate th…

cs.CV2022★ 20 cited

UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning

Yongzhen Wang, Xuefeng Yan, Fu Lee Wang +4

While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known d…

cs.CV2022★ 2 cited

When A Conventional Filter Meets Deep Learning: Basis Composition Learning on Image Filters

Fu Lee Wang, Yidan Feng, Haoran Xie +2

Image filters are fast, lightweight and effective, which make these conventional wisdoms preferable as basic tools in vision tasks. In practical scenarios, users have to tweak para…

cs.IR2020★ 3 cited

Context Reinforced Neural Topic Modeling over Short Texts

Jiachun Feng, Zusheng Zhang, Cheng Ding +2

As one of the prevalent topic mining tools, neural topic modeling has attracted a lot of interests for the advantages of high efficiency in training and strong generalisation abili…

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