3 accepted papers
Directly processing large point clouds is inefficient. State-of-the-art frameworks hierarchically employ Farthest Point Sampling (FPS) to down-sample the data for point cloud classification, semantic segmentation, etc. However, using only geometric information, FPS neglects the importance of semanti…
Due to the advantages of real-time detection and improved performance, single-shot detectors have gained great attention recently. To solve the complex scale variations, single-shot detectors make scale-aware predictions based on multiple pyramid layers. However, the features in the pyramid are not…
Aggregating multi-level features is essential for capturing multi-scale context information for precise scene semantic segmentation. However, the improvement by directly fusing shallow features and deep features becomes limited as the semantic gap between them increases. To solve this problem, we ex…