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Found 7 papers, 3 papers with code
PointAttN: You Only Need Attention for Point Cloud Completion
To solve the problems, we leverage the cross-attention and self-attention mechanisms to design novel neural network for processing point cloud in a per-point manner to eliminate kNNs.
Collaborative Visual Inertial SLAM for Multiple Smart Phones
Each agent can independently explore the environment, run a visual-inertial odometry module online, and then send all the measurement information to a central server with higher computing resources.
Graph Attention Tracking
We propose to establish part-to-part correspondence between the target and the search region with a complete bipartite graph, and apply the graph attention mechanism to propagate target information from the template feature to the search feature.
Consistency-Aware Graph Network for Human Interaction Understanding
Compared with the progress made on human activity classification, much less success has been achieved on human interaction understanding (HIU).
Improving auto-encoder novelty detection using channel attention and entropy minimization
Novelty detection is a important research area which mainly solves the classification problem of inliers which usually consists of normal samples and outliers composed of abnormal samples.
SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking
The proposed framework SiamCAR consists of two simple subnetworks: one Siamese subnetwork for feature extraction and one classification-regression subnetwork for bounding box prediction.
End-to-end feature fusion siamese network for adaptive visual tracking
Both features and the channel weights are utilized in a template generation layer to generate a discriminative template.
