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Found 5 papers, 2 papers with code
STARFlow: Spatial Temporal Feature Re-embedding with Attentive Learning for Real-world Scene Flow
Scene flow prediction is a crucial underlying task in understanding dynamic scenes as it offers fundamental motion information.
GMA3D: Local-Global Attention Learning to Estimate Occluded Motions of Scene Flow
Scene flow represents the motion information of each point in the 3D point clouds.
A channel attention based MLP-Mixer network for motor imagery decoding with EEG
Convolutional neural networks (CNNs) and their variants have been successfully applied to the electroencephalogram (EEG) based motor imagery (MI) decoding task.
Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images
To this end, we propose a novel Two-stage Self-supervised Cycle-consistency Network (TSCNet) for MR slice interpolation, in which a two-stage self-supervised learning (SSL) strategy is developed for unsupervised DL network training.
Reconstruction of Quantitative Susceptibility Maps from Phase of Susceptibility Weighted Imaging with Cross-Connected $Ψ$-Net
In this work, we propose to explore a new value of the high-pass filtered phase data generated in susceptibility weighted imaging (SWI), and develop an end-to-end Cross-connected $\Psi$-Net (C$\Psi$-Net) to reconstruct QSM directly from these phase data in SWI without additional pre-processing.
