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Found 5 papers, 2 papers with code
Automatic Depression Detection via Learning and Fusing Features from Visual Cues
Depression is one of the most prevalent mental disorders, which seriously affects one's life.
Decoupled Low-light Image Enhancement
On the other hand, since the parameter matrix learned from the first stage is aware of the lightness distribution and the scene structure, it can be incorporated into the second stage as the complementary information.
Few-shot Learning with Global Relatedness Decoupled-Distillation
To overcome these problems, we propose a new Global Relatedness Decoupled-Distillation (GRDD) method using the global category knowledge and the Relatedness Decoupled-Distillation (RDD) strategy.
Few-shot Partial Multi-view Learning
The challenges of this task are twofold: (1) under the interference of the missing views, it is difficult to overcome the negative impact brought by data scarcity; (2) the limited number of data exacerbates information scarcity, thereby making it harder to address the view-missing problem.
Real-time Semantic Segmentation via Spatial-detail Guided Context Propagation
In SGCPNet, we propose the strategy of spatial-detail guided context propagation.
