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Ilwi Yun

2 accepted papers

2023

EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation

ICCV 2023poster

Estimating the depths of equirectangular (i.e., 360) images (EIs) is challenging given the distorted 180 x 360 field-of-view, which is hard to be addressed via convolutional neural network (CNN). Although a transformer with global attention achieves significant improvements over CNN for EI depth est…

Cited by 23PDFScholar
2022

Improving 360 Monocular Depth Estimation via Non-local Dense Prediction Transformer and Joint Supervised and Self-Supervised Learning

AAAI 2022technical

Due to difficulties in acquiring ground truth depth of equirectangular (360) images, the quality and quantity of equirectangular depth data today is insufficient to represent the various scenes in the world. Therefore, 360 depth estimation studies, which relied solely on supervised learning, are des…

Cited by 38SourcePDFScholar