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Found 4 papers, 0 papers with code
A Novel Unsupervised Domain Adaption Method for Depth-Guided Semantic Segmentation Using Coarse-to-Fine Alignment
Domain adaptation methods in machine learning deal with the domain shift issue by aligning source and target data representation.
Ranked #12 on
Unsupervised Domain Adaptation
on SYNTHIA-to-Cityscapes
ViTransPAD: Video Transformer using convolution and self-attention for Face Presentation Attack Detection
Instead of using coarse image patches with single-scale as in ViT, we propose the Multi-scale Multi-Head Self-Attention (MsMHSA) architecture to accommodate multi-scale patch partitions of Q, K, V feature maps to the heads of transformer in a coarse-to-fine manner, which enables to learn a fine-grained representation to perform pixel-level discrimination for face PAD.
Predicting Brain Degeneration with a Multimodal Siamese Neural Network
We also show the superiority of the multimodal architecture, for up to 37. 5\% of missing values in test set subjects' clinical measurements, compared to a model using only the clinical modality.
A Survey On Anti-Spoofing Methods For Face Recognition with RGB Cameras of Generic Consumer Devices
The widespread deployment of face recognition-based biometric systems has made face Presentation Attack Detection (face anti-spoofing) an increasingly critical issue.
