Scene Depth Estimation from Traditional Oriental Landscape Paintings

no code implementations • 6 Mar 2024 • Sungho Kang, YeongHyeon Park, Hyunkyu Park, Juneho Yi

To address the problem of scene depth estimation from oriental landscape painting images, we propose a novel framework that consists of two-step Image-to-Image translation method with CLIP-based image matching at the front end to predict the real scene image that best matches with the given oriental landscape painting image.

Depth Estimation Image-to-Image Translation

Excision And Recovery: Visual Defect Obfuscation Based Self-Supervised Anomaly Detection Strategy

no code implementations • 6 Oct 2023 • YeongHyeon Park, Sungho Kang, Myung Jin Kim, Yeonho Lee, Hyeong Seok Kim, Juneho Yi

To enhance the UAD performance, reconstruction-by-inpainting based methods have recently been investigated, especially on the masking strategy of suspected defective regions.

Self-Supervised Anomaly Detection Supervised Anomaly Detection +1

Neural Network Training Strategy to Enhance Anomaly Detection Performance: A Perspective on Reconstruction Loss Amplification

no code implementations • 28 Aug 2023 • YeongHyeon Park, Sungho Kang, Myung Jin Kim, Hyeonho Jeong, Hyunkyu Park, Hyeong Seok Kim, Juneho Yi

In contrast, we note that containing of generalization ability in reconstruction can also be obtained simply from steep-shaped loss landscape.

Unsupervised Anomaly Detection