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arXiv Computer Vision By Yechan Kim, Dongho Yoon, Jongmin Joo, JongHyun Park, Moongu Jeon

ShadowCast: On-the-Fly Context-Aware Shadow Augmentation for Remote Sensing Image Segmentation

Read the original on arXiv Computer Vision →

ShadowCast is a novel on-the-fly, context-aware shadow augmentation method for remote sensing image segmentation. It synthesizes shadows by extracting masks of elevated objects from segmentation labels and projecting synthetic shadows along an inferred cast-shadow direction, without requiring additional networks or metadata. Experiments on Vaihingen, Potsdam, and LoveDA demonstrate consistent performance gains across various state-of-the-art segmentation architectures and when combined with standard augmentation and regularization techniques.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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