Abstract: Kernel point convolution (KPConv) defines convolutional weights based on Euclidean distances between kernel points and input points and has shown good segmentation results on several ...
Abstract: With the impressive achievements of chatGPT and Sora, generative artificial intelligence (GAI) has received increasing attention. Not limited to the field of content generation, GAI is also ...
Abstract: Existing airborne laser scanning (ALS) point cloud semantic segmentation approaches are limited by their overreliances on sufficient point-wise annotations that further confine their ...
Abstract: Learning-based point cloud registration has achieved great success in recent years but is still limited by its generalization. The performance of these methods declines when they are ...
Abstract: Obtaining defect-free point cloud data is challenging due to performance constraints of acquisition devices and unavoidable occlusion, making point cloud data completion critical. In recent ...
Abstract: Recent years have witnessed the success of the deep learning-based technique in research of no-reference point cloud quality assessment (NR-PCQA). For a more accurate quality prediction, ...
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