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Found 5 papers, 2 papers with code
Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach
The optical flow channel is applied to capture the pattern of relative motion between adjacent camera frames and modelled by Spatial-Temporal Graph Convolutional Network (ST-GCN).
Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing
Face anti-spoofing (a. k. a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems.
Ranked #2 on
Face Anti-Spoofing
on MSU-MFSD
Enhancement of land-use change modeling using convolutional neural networks and convolutional denoising autoencoders
This study applies convolutional neural networks (CNN) to capture neighborhood characteristics from satellite images and to enhance the performance of LUC modeling.
Prototype-guided Cross-modal Completion and Alignment for Incomplete Text-based Person Re-identification
Therefore, we propose the cross-modal nearest neighbor construction strategy for missing data by computing the cross-modal similarity between existing images and texts, which provides key guidance for the completion of missing modal features.
End-to-end Rain Streak Removal with RAW Images
To be specific, we generate rainy RAW data by converting color rain streak into RAW space and design simple but efficient RAW processing algorithms to synthesize both rainy and clean color images.
