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Found 5 papers, 5 papers with code
Clustering Propagation for Universal Medical Image Segmentation
}$ This enables knowledge acquired from prior slices to assist in the segmentation of the current slice, further efficiently bridging the communication between remote slices using mere 2D networks.
PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences
Then, a spatial convolution is employed to capture the local structure of points in the 3D space, and a temporal convolution is used to model the dynamics of the spatial regions along the time dimension.
Ranked #3 on
3D Action Recognition
on NTU RGB+D
Modeling the Probabilistic Distribution of Unlabeled Data forOne-shot Medical Image Segmentation
Thus, it is more desirable to employ only a few labeled data in pursuing high segmentation performance.
RFNet: Region-Aware Fusion Network for Incomplete Multi-Modal Brain Tumor Segmentation
In this work, we propose a Region-aware Fusion Network (RFNet) that is able to exploit different combinations of multi-modal data adaptively and effectively for tumor segmentation.
Ranked #69 on
Semantic Segmentation
on NYU Depth v2
Adaptive Exploration for Unsupervised Person Re-Identification
However, a problem of the adaptive selection is that, when an image has too many neighborhoods, it is more likely to attract other images as its neighborhoods.
