Search Results for author:
Found 5 papers, 0 papers with code
Latent-based Diffusion Model for Long-tailed Recognition
We propose a new approach, the Latent-based Diffusion Model for Long-tailed Recognition (LDMLR), as a feature augmentation method to tackle the issue.
Feature Correlation Aggregation: on the Path to Better Graph Neural Networks
The core concept of GNNs is to find a representation by recursively aggregating the representations of a central node and those of its neighbors.
Channel Recurrent Attention Networks for Video Pedestrian Retrieval
Full attention, which generates an attention value per element of the input feature maps, has been successfully demonstrated to be beneficial in visual tasks.
Cross-Correlated Attention Networks for Person Re-Identification
Deep neural networks need to make robust inference in the presence of occlusion, background clutter, pose and viewpoint variations -- to name a few -- when the task of person re-identification is considered.
Dynamic risk measures with fluctuation of market volatility under Bochne-Lebesgue space
Starting from the global financial crisis to the more recent disruptions brought about by geopolitical tensions and public health crises, the volatility of risk in financial markets has increased significantly.
