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Found 4 papers, 2 papers with code
Learning CNN on ViT: A Hybrid Model to Explicitly Class-specific Boundaries for Domain Adaptation
Compared to conventional DA methods, our ECB achieves superior performance, which verifies its effectiveness in this hybrid model.
Ranked #3 on
Unsupervised Domain Adaptation
on Office-Home
C2T-Net: Channel-Aware Cross-Fused Transformer-Style Networks for Pedestrian Attribute Recognition
Our performance on the PETA dataset remains competitive, standing on par with other cutting-edge models.
Ranked #2 on
Pedestrian Attribute Recognition
on PETA
Towards Robust Natural-Looking Mammography Lesion Synthesis on Ipsilateral Dual-Views Breast Cancer Analysis
In recent years, many mammographic image analysis methods have been introduced for improving cancer classification tasks.
Improved Knowledge Transfer for Semi-Supervised Domain Adaptation via Trico Training Strategy
The first co-training strategy exploits a correlation between MLP and inter-view GCN classifiers to minimize the inter-domain discrepancy, in which the inter-view GCN classifier provides its pseudo labels to teach the MLP classifier, which encourages class representation alignment across domains.
