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Found 3 papers, 2 papers with code
Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognition
Unifying the MSST module, a multi-scale spatial–temporal convolutional neural network (MSSTNet) is proposed to capture high-level spatial–temporal semantic features for action recognition.
Ranked #2 on
Skeleton Based Action Recognition
on UAV-Human
Few-shot Medical Image Segmentation via Cross-Reference Transformer
We first enhance the correlation features between the support set image and the query image using a bidirectional cross-attention module.
Neural Spatio-Temporal Beamformer for Target Speech Separation
Purely neural network (NN) based speech separation and enhancement methods, although can achieve good objective scores, inevitably cause nonlinear speech distortions that are harmful for the automatic speech recognition (ASR).
Audio and Speech Processing Sound
