arXiv:1611.07709
공식 코드 · Papers with Code
Fully Convolutional Instance-aware Semantic Segmentation
원문 초록
We present the first fully convolutional end-to-end solution for instance-aware semantic segmentation task. It inherits all the merits of FCNs for semantic segmentation and instance mask proposal. It performs instance mask prediction and classification jointly. The underlying convolutional representation is fully shared between the two sub-tasks, as well as between all regions of interest. The proposed network is highly integrated and achieves state-of-the-art performance in both accuracy and efficiency. It wins the COCO 2016 segmentation competition by a large margin. Code would be released at \url{https://github.com/daijifeng001/TA-FCN}.
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No time to train! Training-Free Reference-Based Instance Segmentation
NOCTIS: Novel Object Cyclic Threshold based Instance Segmentation
SCORE: Scene Context Matters in Open-Vocabulary Remote Sensing Instance Segmentation
Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation
A Novel Deep Learning Approach Featuring Graph-Based Algorithm for Cell Segmentation and Tracking
GIN: Generative INvariant Shape Prior for Amodal Instance Segmentation
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