Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Numerous existing object segmentation frameworks commonly utilize the object bounding box as a prior. ,  address semantic segmentation assuming that object bounding boxes are provided by object detectors, but no training data with annotated segments are available. Based on a set of segment hypotheses,  introduce a simple voting scheme to estimate shape guidance for each bounding box. The derived shape guidance is used in the subsequent graph-cut-based figure-ground segmentation. The final segmentation result is obtained by merging the segmentation results in the bounding boxes.  conduct an extensive analysis of the effect of object bounding box accuracy. Comprehensive experiments on both the challenging PASCAL VOC object segmentation dataset and GrabCut-50 image segmentation dataset show that the proposed approach achieves competitive results compared to previous detection or bounding box prior based methods, as ll as other state-of-the-art semantic segmentation methods.
['Wei Xia', 'Csaba Domokos', 'Jian Dong', 'Loong-Fah Cheong', 'Shuicheng Yan']
I am writing a research paper on a idea Semantic Segmentation without Annotating Segments
[{"from": "human", "value": "I am writing a research paper on a idea Semantic Segmentation without Annotating Segments"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Numerous existing object segmentation frameworks commonly utilize the object bounding box as a prior. ,  address semantic segmentation assuming that object bounding boxes are provided by object detectors, but no training data with annotated segments are available. Based on a set of segment hypotheses,  introduce a simple voting scheme to estimate shape guidance for each bounding box. The derived shape guidance is used in the subsequent graph-cut-based figure-ground segmentation. The final segmentation result is obtained by merging the segmentation results in the bounding boxes.  conduct an extensive analysis of the effect of object bounding box accuracy. Comprehensive experiments on both the challenging PASCAL VOC object segmentation dataset and GrabCut-50 image segmentation dataset show that the proposed approach achieves competitive results compared to previous detection or bounding box prior based methods, as ll as other state-of-the-art semantic segmentation methods."}]