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Found 5 papers, 3 papers with code
A Multilevel Guidance-Exploration Network and Behavior-Scene Matching Method for Human Behavior Anomaly Detection
Human behavior anomaly detection aims to identify unusual human actions, playing a crucial role in intelligent surveillance and other areas.
A Self-Training Framework Based on Multi-Scale Attention Fusion for Weakly Supervised Semantic Segmentation
Weakly supervised semantic segmentation (WSSS) based on image-level labels is challenging since it is hard to obtain complete semantic regions.
UrbanBIS: a Large-scale Benchmark for Fine-grained Urban Building Instance Segmentation
Besides, we propose B-Seg, a building instance segmentation method to establish UrbanBIS.
CM-MLP: Cascade Multi-scale MLP with Axial Context Relation Encoder for Edge Segmentation of Medical Image
However, those methods have the following challenges when dealing with the edges of the medical images: (1) Previous convolutional-based methods do not focus on the boundary relationship between foreground and background around the segmentation edge, which leads to the degradation of segmentation performance when the edge changes complexly.
PBRnet: Pyramidal Bounding Box Refinement to Improve Object Localization Accuracy
Based on these principles, we designed a novel boundary refinement architecture to improve localization accuracy by combining coarse-to-fine framework with feature pyramid structure, named as Pyramidal Bounding Box Refinement network(PBRnet), which parameterizes gradually focused boundary areas of objects and leverages lower-level feature maps to extract finer local information when refining the predicted bounding boxes.
