
EAGLE introduces a novel approach emphasizing object-centric representation learning for unsupervised semantic segmentation, addressing the lack of explicit object-level semantic encoding in patch-level features. By incorporating EiCue and object-centric contrastive loss, the model enhances semantic accuracy across complex scenes.


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EAGLE-Eigen-Aggregation-Learning-for-Object-Centric-Unsupervised-Semantic-Segmentation


EAGLE: Eigen Aggregation Learning for Object-Centric Unsupervised Semantic Segmentation


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EAGLE introduces object-centric representation learning for unsupervised semantic segmentation, addressing the challenge of complex object segmentation.


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EAGLE betont die objektzentrierte Repräsentationslernen für die unüberwachte semantische Segmentierung.
