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Chih-Chung Hsu

4 papers hereh-index 28 citations7 works total

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

author position
  • first author1
  • middle author1
  • last author2

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

fields
  • cs.CV4
same name
  • Chih-Chung Hsu — 28 papers, h 12
  • Chih-Chung Hsu — 1 paper, h 0
  • Chih-Chung Hsu — 1 paper, 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

collaborators

4 papers

cs.CV2026

VReID-XFD: Video-based Person Re-identification at Extreme Far Distance Challenge Results

Kailash A. Hambarde, Hugo Proença, Md Rashidunnabi +18

Person re-identification (ReID) across aerial and ground views at extreme far distances introduces a distinct operating regime where severe resolution degradation, extreme viewpoin…

cs.CV2025

ChangeDINO: DINOv3-Driven Building Change Detection in Optical Remote Sensing Imagery

Ching-Heng Cheng, Chih-Chung Hsu

Remote sensing change detection (RSCD) aims to identify surface changes from co-registered bi-temporal images. However, many deep learning-based RSCD methods rely solely on change-…

cs.CV2025

WWE-UIE: A Wavelet & White Balance Efficient Network for Underwater Image Enhancement

Ching-Heng Cheng, Jen-Wei Lee, Chia-Ming Lee +1

Underwater Image Enhancement (UIE) aims to restore visibility and correct color distortions caused by wavelength-dependent absorption and scattering. Recent hybrid approaches, whic…

cs.CV2025

Technical Report for ICRA 2025 GOOSE 2D Semantic Segmentation Challenge: Leveraging Color Shift Correction, RoPE-Swin Backbone, and Quantile-based Label Denoising Strategy for Robust Outdoor Scene Understanding

Chih-Chung Hsu, I-Hsuan Wu, Wen-Hai Tseng +4

This report presents our semantic segmentation framework developed by team ACVLAB for the ICRA 2025 GOOSE 2D Semantic Segmentation Challenge, which focuses on parsing outdoor scene…

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