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20192026
most citedMulti-Stage Pathological Image Classification using Semantic Segmentation

7 citations · 22 across the 10 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results

Shuhong Liu, Chenyu Bao, Ziteng Cui +103

This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to…

cs.CV2026

RealX3D: A Physically-Degraded 3D Benchmark for Multi-view Visual Restoration and Reconstruction

Shuhong Liu, Chenyu Bao, Ziteng Cui +11

We introduce RealX3D, a real-capture benchmark for multi-view visual restoration and 3D reconstruction under diverse physical degradations. RealX3D groups corruptions into four fam…

cs.CV2023

Domain Adaptive Multiple Instance Learning for Instance-level Prediction of Pathological Images

Shusuke Takahama, Yusuke Kurose, Yusuke Mukuta +7

Pathological image analysis is an important process for detecting abnormalities such as cancer from cell images. However, since the image size is generally very large, the cost of…

cs.CV2023★ 6 cited

Sketch-based Medical Image Retrieval

Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya +12

The amount of medical images stored in hospitals is increasing faster than ever; however, utilizing the accumulated medical images has been limited. This is because existing conten…

cs.CV2021★ 2 cited

Decomposing Normal and Abnormal Features of Medical Images into Discrete Latent Codes for Content-Based Image Retrieval

Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose +5

In medical imaging, the characteristics purely derived from a disease should reflect the extent to which abnormal findings deviate from the normal features. Indeed, physicians ofte…