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Tatsuya Harada

6 papers hereh-index 5306 citations12 works total

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

author position
  • middle author4
  • last author2

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL1
  • eess.IV1
same name
  • Tatsuya Harada — 21 papers, h 10
  • Tatsuya Harada — 17 papers, h 4
  • Tatsuya Harada — 16 papers, h 12
  • Tatsuya Harada — 12 papers, h 8
  • Tatsuya Harada — 7 papers, h 4
  • Tatsuya Harada — 3 papers, h 3

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
20232025
most citedFrequency-aware Feature Fusion for Dense Image Prediction

3 citations · 3 across the 6 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2025

Discovering an Image-Adaptive Coordinate System for Photography Processing

Ziteng Cui, Lin Gu, Tatsuya Harada

Curve & Lookup Table (LUT) based methods directly map a pixel to the target output, making them highly efficient tools for real-time photography processing. However, due to extreme…

cs.CV2025

Emergence of Painting Ability via Recognition-Driven Evolution

Yi Lin, Lin Gu, Ziteng Cui +5

From Paleolithic cave paintings to Impressionism, human painting has evolved to depict increasingly complex and detailed scenes, conveying more nuanced messages. This paper attempt…

cs.CV2024

Paleoinspired Vision: From Exploring Colour Vision Evolution to Inspiring Camera Design

Junjie Zhang, Zhimin Zong, Lin Gu +8

The evolution of colour vision is captivating, as it reveals the adaptive strategies of extinct species while simultaneously inspiring innovations in modern imaging technology. In…

cs.CV2024★ 3 cited

Frequency-aware Feature Fusion for Dense Image Prediction

Linwei Chen, Ying Fu, Lin Gu +3

Dense image prediction tasks demand features with strong category information and precise spatial boundary details at high resolution. To achieve this, modern hierarchical models o…

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