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Found 7 papers, 1 papers with code
CDSA: Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
In order to jointly capture the self-attention across multiple dimensions, including time, location and the sensor measurements, while maintain low computational complexity, we propose a novel approach called Cross-Dimensional Self-Attention (CDSA) to process each dimension sequentially, yet in an order-independent manner.
Online Detection of Action Start in Untrimmed, Streaming Videos
We aim to tackle a novel task in action detection - Online Detection of Action Start (ODAS) in untrimmed, streaming videos.
Fast Resampling of 3D Point Clouds via Graphs
We use a general feature-extraction operator to represent application-dependent features and propose a general reconstruction error to evaluate the quality of resampling.
Chebyshev and Conjugate Gradient Filters for Graph Image Denoising
In 3D image/video acquisition, different views are often captured with varying noise levels across the views.
Graph Based Skeleton Modeling for Human Activity Analysis
Understanding human activity based on sensor information is required in many applications and has been an active research area.
Ranked #4 on
Skeleton Based Action Recognition
on MSR Action3D
Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation
In order to impute the missing values, state-of-the-art methods are built on Recurrent Neural Networks (RNN), which process each time stamp sequentially, prohibiting the direct modeling of the relationship between distant time stamps.
Graph Signal Processing for Geometric Data and Beyond: Theory and Applications
Geometric data acquired from real-world scenes, e. g., 2D depth images, 3D point clouds, and 4D dynamic point clouds, have found a wide range of applications including immersive telepresence, autonomous driving, surveillance, etc.
