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Found 9 papers, 5 papers with code
Pyramid Diffusion for Fine 3D Large Scene Generation
Directly transferring the 2D techniques to 3D scene generation is challenging due to significant resolution reduction and the scarcity of comprehensive real-world 3D scene datasets.
Gradient-based adaptive wavelet de-noising method for photoacoustic imaging in vivo
The proposed de-noising method provides potential to improve the SNR of PA signal under single-shot low-power laser illumination for biomedical applications in vivo.
Risk-optimized Outlier Removal for Robust 3D Point Cloud Classification
With the growth of 3D sensing technology, deep learning system for 3D point clouds has become increasingly important, especially in applications like autonomous vehicles where safety is a primary concern.
Primitive3D: 3D Object Dataset Synthesis from Randomly Assembled Primitives
Further study suggests that our strategy can improve the model performance by pretraining and fine-tuning scheme, especially for the dataset with a small scale.
Directed Graph Contrastive Learning
However, it is still in its infancy with two concerns: 1) changing the graph structure through data augmentation to generate contrastive views may mislead the message passing scheme, as such graph changing action deprives the intrinsic graph structural information, especially the directional structure in directed graphs; 2) since GCL usually uses predefined contrastive views with hand-picking parameters, it does not take full advantage of the contrastive information provided by data augmentation, resulting in incomplete structure information for models learning.
PointBA: Towards Backdoor Attacks in 3D Point Cloud
We present the backdoor attacks in 3D point cloud with a unified framework that exploits the unique properties of 3D data and networks.
Integrated Age Estimation Mechanism
Traditional age estimation mechanism focuses estimation age error, but ignores that there is a deviation between the estimated age and real age due to disease.
Digraph Inception Convolutional Networks
Graph Convolutional Networks (GCNs) have shown promising results in modeling graph-structured data.
Campus3D: A Photogrammetry Point Cloud Benchmark for Hierarchical Understanding of Outdoor Scene
Based on it, we formulate a hierarchical learning problem for 3D point cloud segmentation and propose a measurement evaluating consistency across various hierarchies.
