Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Research works on the two topics of Semantic Segmentation and SLAM Simultaneous Localization and Mapping have been following separate tracks. Here,  link them quite tightly by delineating a category label fusion technique that allows for embedding semantic information into the dense map created by a volume-based SLAM algorithm such as KinectFusion. Accordingly, our approach is the first to provide a semantically labeled dense reconstruction of the environment from a stream of RGB-D images.  validate our proposal using a publicly available semantically annotated RGB-D dataset and a employing ground truth labels, b corrupting such annotations with synthetic noise, ci¾?deploying a state of the art semantic segmentation algorithm based on Convolutional Neural Networks.
['Tommaso Cavallari', 'Luigi Di Stefano']
I am writing a research paper on a idea Volume-Based Semantic Labeling with Signed Distance Functions
[{"from": "human", "value": "I am writing a research paper on a idea Volume-Based Semantic Labeling with Signed Distance Functions"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Research works on the two topics of Semantic Segmentation and SLAM Simultaneous Localization and Mapping have been following separate tracks. Here,  link them quite tightly by delineating a category label fusion technique that allows for embedding semantic information into the dense map created by a volume-based SLAM algorithm such as KinectFusion. Accordingly, our approach is the first to provide a semantically labeled dense reconstruction of the environment from a stream of RGB-D images.  validate our proposal using a publicly available semantically annotated RGB-D dataset and a employing ground truth labels, b corrupting such annotations with synthetic noise, ci\u00be?deploying a state of the art semantic segmentation algorithm based on Convolutional Neural Networks."}]