A deep learning model decomposes and reconstructs spatial correlation maps from sparse samples using attention and multi-scale fusion, reporting cosine similarity above 0.8 on the CKMImageNet dataset.
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2026 3verdicts
UNVERDICTED 3representative citing papers
A new framework generates part-level animatable 3D Gaussian vehicles from images by adding modules for exclusive part ownership and kinematic joint/axis prediction.
SPL unifies unsupervised and sparsely-supervised 3D object detection via semantic pseudo-labeling that produces bounding boxes and point labels, followed by memory-based prototype learning that mines features from both labeled and unlabeled data.
citing papers explorer
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CKM Beyond Channel Gain: Spatial Correlation Map Construction with Deep Learning
A deep learning model decomposes and reconstructs spatial correlation maps from sparse samples using attention and multi-scale fusion, reporting cosine similarity above 0.8 on the CKMImageNet dataset.
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Part-Level 3D Gaussian Vehicle Generation with Joint and Hinge Axis Estimation
A new framework generates part-level animatable 3D Gaussian vehicles from images by adding modules for exclusive part ownership and kinematic joint/axis prediction.
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Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learning
SPL unifies unsupervised and sparsely-supervised 3D object detection via semantic pseudo-labeling that produces bounding boxes and point labels, followed by memory-based prototype learning that mines features from both labeled and unlabeled data.