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What is: Conditional Convolutions for Instance Segmentation?

SourceConditional Convolutions for Instance Segmentation
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

CondInst is a simple yet effective instance segmentation framework. It eliminates ROI cropping and feature alignment with the instance-aware mask heads. As a result, CondInst can solve instance segmentation with fully convolutional networks. CondInst is able to produce high-resolution instance masks without longer computational time. Extensive experiments show that CondInst can achieve even better performance and inference speed than Mask R-CNN. It can be a strong alternative to previous ROI-based instance segmentation methods. Code is at https://github.com/aim-uofa/AdelaiDet.