Most segmentation models are trained on urban datasets (Cityscapes, ADE20K) and fail catastrophically in desert terrain — where there are no lane markings, few rigid objects, and extreme texture ...

Abstract: Large vision-language models revolutionized image classification and semantic segmentation paradigms. However, they typically assume a pre-defined set of categories, or vocabulary, at test ...

Abstract: We explore the potential of pretrain-and-finetune manner on the RGB-D semantic segmentation to solve the common mismatch problem in this field. Specifically, we present DFormer++, a novel ...

Supply chain disruptions surged 38% in 2024, yet most manufacturers take two weeks to respond when they have just 72 hours to avoid major impact. Semantic intelligence can compress this reaction time ...

Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image ...