Supplementary Material for Semantic Instance Annotation of Street Scenes by 3D to 2D Label Transfer
نویسندگان
چکیده
This supplementary material provides additional illustrations, visualizations and experiments. We start by showing the color coding and label mapping used for the semantic and instance label results in the paper. Then we provide more details about the 3D fold/curb detection and parameter settings that are used in the paper. Next, we provide additional quantitative and qualitative semi-dense inference results for both semantic and instance segmentation. Finally, we show the ability of our method to annotate 3D point clouds with semantic and instance labels which is a byproduct of our approach. 1. Color Coding We first illustrate the color coding which we have used for Fig. 1 and Fig. 5 in the main paper in Fig. 1. Road Driveway Sidewalk Terrain Vegetation Building Car Trailer Caravan Box Gate Wall Fence Sky Undefined (a) Color Coding of Semantic Labels. Road Driveway Sidewalk Terrain Vegetation Building Car Trailer Caravan Box Gate Wall Fence Sky Garage Truck Undefined (b) Color Coding of Instance Labels. Figure 1: Color Coding. Illustration of color coding used for Fig. 1 and Fig. 5 in the main paper.
منابع مشابه
Supervised Label Transfer for Semantic Segmentation of Street Scenes
In this paper, we propose a robust supervised label transfer method for the semantic segmentation of street scenes. Given an input image of street scene, we first find multiple image sets from the training database consisting of images with annotation, each of which can cover all semantic categories in the input image. Then, we establish dense correspondence between the input image and each fou...
متن کاملA Robust 3D-2D Interactive Tool for Scene Segmentation and Annotation
Recent advances of 3D acquisition devices have enabled large-scale acquisition of 3D scene data. Such data, if completely and well annotated, can serve as useful ingredients for a wide spectrum of computer vision and graphics works such as data-driven modeling and scene understanding, object detection and recognition. However, annotating a vast amount of 3D scene data remains challenging due to...
متن کاملSemantic annotation for complex video street views based on 2D-3D multi-feature fusion and aggregated boosting decision forests
Accurate and efficient semantic annotation is an important but difficult step in large-scale video interpretation. This paper presents a novel framework based on 2D–3D multi-feature fusion and aggregated boosting decision forest (ABDF) for semantic annotation of video street views. We first integrate the 3D and 2D features to define the appearance model for characterizing the different types of...
متن کاملDeep Supervision with Shape Concepts for Occlusion-Aware 3D Object Parsing – Supplementary Material
In this supplementary material, Section 2 details the 3D annotation for CAD models and real images as well as our approach to compute the car yaw angle given a 3D skeleton. Next, in Section 3, we present the instance segmentation algorithm in detail for our experiments on PASCAL3D+. Finally, we provide more quantitative results on KITTI-3D in Section 4 and demonstrate more qualitative results o...
متن کاملHarvesting Multiple Views for Marker-less 3D Human Pose Annotations Supplementary Material
In this supplementary, we provide material that could not be included in the main manuscript due to space constraints. Section 1 provides additional quantitative evaluation of our approach for multi-view pose estimation, and comparison with the state-of-the-art for HumanEva-I [4]. Section 2 provides full results of the multi-view optimization on Human3.6M after refining the generic 2D pose Conv...
متن کامل