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Rakesh Ranjan

4 papers hereh-index 358 citations6 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
  • Rakesh Ranjan — 15 papers, h 9
  • Rakesh Ranjan — 11 papers, h 9
  • Rakesh Ranjan — 7 papers, h 4
  • Rakesh Ranjan — 5 papers, h 4
  • Rakesh Ranjan — 4 papers, h 4
  • Rakesh Ranjan — 3 papers, h 2

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 citedHierarchical Information Flow for Generalized Efficient Image Restoration

1 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

Fractal-IR: A Unified Framework for Efficient and Scalable Image Restoration

Yawei Li, Bin Ren, Jingyun Liang +5

While vision transformers achieve significant breakthroughs in various image restoration (IR) tasks, it is still challenging to efficiently scale them across multiple types of degr…

cs.CV2024★ 1 cited

Hierarchical Information Flow for Generalized Efficient Image Restoration

Yawei Li, Bin Ren, Jingyun Liang +5

While vision transformers show promise in numerous image restoration (IR) tasks, the challenge remains in efficiently generalizing and scaling up a model for multiple IR tasks. To…

cs.CV2024★ 1 cited

Sharing Key Semantics in Transformer Makes Efficient Image Restoration

Bin Ren, Yawei Li, Jingyun Liang +6

Image Restoration (IR), a classic low-level vision task, has witnessed significant advancements through deep models that effectively model global information. Notably, the emergenc…

cs.CV2024

Key-Graph Transformer for Image Restoration

Bin Ren, Yawei Li, Jingyun Liang +5

While it is crucial to capture global information for effective image restoration (IR), integrating such cues into transformer-based methods becomes computationally expensive, espe…

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