Results 11 to 20 of about 6,190,166 (311)
AIRBORNE LIDAR POINT CLOUD CLASSIFICATION FUSION WITH DIM POINT CLOUD [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Airborne Light Detection And Ranging (LiDAR) point clouds and images data fusion have been widely studied. However, with recent developments in photogrammetric technology, images can now provide dense image matching (DIM) point clouds.
M. Zhou, Z. Kang, Z. Wang, M. Kong
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PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers [PDF]
IEEE International Conference on Computer Vision, 2021 Point clouds captured in real-world applications are of-ten incomplete due to the limited sensor resolution, single viewpoint, and occlusion. Therefore, recovering the complete point clouds from partial ones becomes an indispensable task in many ...
Xumin Yu +5 more
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Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training [PDF]
Neural Information Processing Systems, 2022 Masked Autoencoders (MAE) have shown great potentials in self-supervised pre-training for language and 2D image transformers. However, it still remains an open question on how to exploit masked autoencoding for learning 3D representations of irregular ...
Renrui Zhang +7 more
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Diffusion Probabilistic Models for 3D Point Cloud Generation [PDF]
Computer Vision and Pattern Recognition, 2021 We present a probabilistic model for point cloud generation, which is fundamental for various 3D vision tasks such as shape completion, upsampling, synthesis and data augmentation.
Shitong Luo, Wei Hu
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PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency [PDF]
Computer Vision and Pattern Recognition, 2021 Removing outlier correspondences is one of the critical steps for successful feature-based point cloud registration. Despite the increasing popularity of introducing deep learning techniques in this field, spatial consistency, which is essentially ...
Xuyang Bai +7 more
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Three-dimensional Point Cloud Model Segmentation Based on Significance and Weak Convexity [PDF]
Jisuanji gongcheng, 2018 The existing three-dimensional point cloud model segmentation algorithms cannot segment large components and small components at the same time.Aiming at this problem,in this paper,a segmentation method is proposed based on the significance and weak ...
ZHENG Lele,HAN Huiyan,HAN Xie
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DPDist: Comparing Point Clouds Using Deep Point Cloud Distance [PDF]
, 2020 We introduce a new deep learning method for point cloud comparison. Our approach, named Deep Point Cloud Distance (DPDist), measures the distance between the points in one cloud and the estimated surface from which the other point cloud is sampled. The surface is estimated locally and efficiently using the 3D modified Fisher vector representation.
Urbach, Dahlia +2 more
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VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.
Yin Zhou, Oncel Tuzel
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PointCLIP: Point Cloud Understanding by CLIP [PDF]
Computer Vision and Pattern Recognition, 2021 Recently, zero-shot and few-shot learning via Contrastive Vision-Language Pre-training (CLIP) have shown inspirational performance on 2D visual recognition, which learns to match images with their corresponding texts in open-vocabulary settings. However,
Renrui Zhang +8 more
semanticscholar +1 more source
PointRCNN: 3D Object Proposal Generation and Detection From Point Cloud [PDF]
Computer Vision and Pattern Recognition, 2018 In this paper, we propose PointRCNN for 3D object detection from raw point cloud. The whole framework is composed of two stages: stage-1 for the bottom-up 3D proposal generation and stage-2 for refining proposals in the canonical coordinates to obtain ...
Shaoshuai Shi +2 more
semanticscholar +1 more source