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Found 8 papers, 0 papers with code
Using deep learning for community discovery in social networks
Thanks to spectral clustering which is one of the best community detection methods, the proposed new method is also good at community discovery task.
Robust Medical Instrument Segmentation Challenge 2019
The validation of the competing methods for the three tasks (binary segmentation, multi-instance detection and multi-instance segmentation) was performed in three different stages with an increasing domain gap between the training and the test data.
Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation
Computer vision technology is widely used in biological and medical data analysis and understanding.
2D Amodal Instance Segmentation Guided by 3D Shape Prior
However, masks in 2D space are only some observations and samples from the 3D model in different viewpoints and thus can not represent the real complete physical shape of the instances.
MUVA: A New Large-Scale Benchmark for Multi-View Amodal Instance Segmentation in the Shopping Scenario
To bridge this gap, we propose a new task called Multi-view Amodal Instance Segmentation (MAIS) and introduce the MUVA dataset, the first MUlti-View AIS dataset that takes the shopping scenario as instantiation.
OAFormer: Learning Occlusion Distinguishable Feature for Amodal Instance Segmentation
Hence we believe it is vital for the method to be distinguishable about the degree of occlusion for each instance.
GIN: Generative INvariant Shape Prior for Amodal Instance Segmentation
In human amodal perception, shape-prior knowledge is helpful for AIS.
BLADE: Box-Level Supervised Amodal Segmentation through Directed Expansion
We present a novel solution to tackle this problem by introducing a directed expansion approach from visible masks to corresponding amodal masks.
