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Yi Zou

4 papers hereh-index 224 citations7 works total

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

author position
  • middle author4

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

fields
  • cs.CV4
same name
  • Yi Zou — 4 papers, h 2
  • Yi Zou — 4 papers, h 4
  • Yi Zou — 3 papers, h 4
  • Yi Zou — 2 papers, h 2
  • Yi Zou — 2 papers, h 2
  • Yi Zou — 1 paper, h 0

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 · 1 across the 1 of their papers we have counts for

collaborators

4 papers

cs.CV2026★ 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.CV2025

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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