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Found 11 papers, 6 papers with code
Scatter Ptychography
Coherent illumination reflected by a remote target may be secondarily scattered by intermediate objects or materials.
SequentialPointNet: A strong frame-level parallel point cloud sequence network for 3D action recognition
The key to our approach is to divide the main modeling operations into frame-level units executed in parallel, which greatly improves the efficiency of modeling point cloud sequences. Moreover, we propose to flatten the point cloud sequence into a new point data type named hyperpoint sequence that preserves the complete spatial structure of each frame.
Edge Proposal Sets for Link Prediction
Here, we demonstrate how simply adding a set of edges, which we call a \emph{proposal set}, to the graph as a pre-processing step can improve the performance of several link prediction algorithms.
Ranked #1 on
Link Property Prediction
on ogbl-ddi
Human Action Recognition Based on Multi-scale Feature Maps from Depth Video Sequences
We employ depth motion images (DMI) as the templates to generate the multi-scale static representation of actions.
Combining Label Propagation and Simple Models Out-performs Graph Neural Networks
Graph Neural Networks (GNNs) are the predominant technique for learning over graphs.
Ranked #14 on
Node Property Prediction
on ogbn-products
Better Set Representations For Relational Reasoning
Incorporating relational reasoning into neural networks has greatly expanded their capabilities and scope.
AttentionAnatomy: A unified framework for whole-body organs at risk segmentation using multiple partially annotated datasets
Organs-at-risk (OAR) delineation in computed tomography (CT) is an important step in Radiation Therapy (RT) planning.
Enhancing Adversarial Example Transferability with an Intermediate Level Attack
We show that we can select a layer of the source model to perturb without any knowledge of the target models while achieving high transferability.
Intermediate Level Adversarial Attack for Enhanced Transferability
Neural networks are vulnerable to adversarial examples, malicious inputs crafted to fool trained models.
Multispectral Image Intrinsic Decomposition via Subspace Constraint
In this paper, a new Multispectral Image Intrinsic Decomposition model (MIID) is presented to decompose the shading and reflectance from a single multispectral image.
Multispectral Image Intrinsic Decomposition via Low Rank Constraint
In this paper, a Low Rank Multispectral Image Intrinsic Decomposition model (LRIID) is presented to decompose the shading and reflectance from a single multispectral image.
