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Guangwei Gao

5 papers hereh-index 335 citations6 works total

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

author position
  • middle author2
  • last author3

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • eess.IV1
same name
  • Guangwei Gao — 11 papers, h 30
  • Guangwei Gao — 8 papers, h 5
  • Guangwei Gao — 7 papers, h 2
  • Guangwei Gao — 7 papers, h 0
  • Guangwei Gao — 5 papers, h 2
  • Guangwei Gao — 4 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

most citedCross Paradigm Representation and Alignment Transformer for Image Deraining

1 citations · 3 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025★ 1 cited

Cross Paradigm Representation and Alignment Transformer for Image Deraining

Shun Zou, Yi Zou, Juncheng Li +2

Transformer-based networks have achieved strong performance in low-level vision tasks like image deraining by utilizing spatial or channel-wise self-attention. However, irregular r…

cs.CV2025

Learning Dual-Domain Multi-Scale Representations for Single Image Deraining

Shun Zou, Yi Zou, Mingya Zhang +3

Existing image deraining methods typically rely on single-input, single-output, and single-scale architectures, which overlook the joint multi-scale information between external an…

cs.CV2025

Fraesormer: Learning Adaptive Sparse Transformer for Efficient Food Recognition

Shun Zou, Yi Zou, Mingya Zhang +3

In recent years, Transformer has witnessed significant progress in food recognition. However, most existing approaches still face two critical challenges in lightweight food recogn…

cs.CV2024★ 1 cited

MambaMIC: An Efficient Baseline for Microscopic Image Classification with State Space Models

Shun Zou, Zhuo Zhang, Yi Zou +1

In recent years, CNN and Transformer-based methods have made significant progress in Microscopic Image Classification (MIC). However, existing approaches still face the dilemma bet…

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