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Found 6 papers, 3 papers with code
Bidirectional Correlation-Driven Inter-Frame Interaction Transformer for Referring Video Object Segmentation
Moreover, a bidirectional vision-language interaction module is implemented before the multimodal Transformer to enhance the correlation between the visual and linguistic features, thus facilitating the language queries to decode more precise object information from visual features and ultimately improving the segmentation performance.
Learning to Learn Better for Video Object Segmentation
Recently, the joint learning framework (JOINT) integrates matching based transductive reasoning and online inductive learning to achieve accurate and robust semi-supervised video object segmentation (SVOS).
Siamese Network with Interactive Transformer for Video Object Segmentation
Semi-supervised video object segmentation (VOS) refers to segmenting the target object in remaining frames given its annotation in the first frame, which has been actively studied in recent years.
Stagewise Unsupervised Domain Adaptation with Adversarial Self-Training for Road Segmentation of Remote Sensing Images
In this paper, we propose a novel stagewise domain adaptation model called RoadDA to address the DS issue in this field.
Transportation Density Reduction Caused by City Lockdowns Across the World during the COVID-19 Epidemic: From the View of High-resolution Remote Sensing Imagery
Considering that public transportation was mostly reduced or even forbidden, our results indicate that city lockdown policies are effective at limiting human transmission within cities.
Defect Detection from UAV Images based on Region-Based CNNs
In this work, we study the performance of the region-based CNN for the electrical equipment defect detection by using the UAV images.
