Search Results for author:
Found 4 papers, 2 papers with code
Kairos: Practical Intrusion Detection and Investigation using Whole-system Provenance
Sifting through their design documents, we identify four common dimensions that drive the development of provenance-based intrusion detection systems (PIDSes): scope (can PIDSes detect modern attacks that infiltrate across application boundaries?
Hierarchical Graph Convolutional Skeleton Transformer for Action Recognition
Graph convolutional networks (GCNs) have emerged as dominant methods for skeleton-based action recognition.
Rethinking the Misalignment Problem in Dense Object Detection
On the basis of SALT and SDR loss, we propose SALT-Net, which explicitly exploits task-aligned point-set features for accurate detection results.
Objects as Extreme Points
We also propose a new metric to measure the similarity between two groups of extreme points, namely, Extreme Intersection over Union (EIoU), and incorporate this EIoU as a new regression loss.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
