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Found 6 papers, 2 papers with code
Comp4D: LLM-Guided Compositional 4D Scene Generation
Recent advancements in diffusion models for 2D and 3D content creation have sparked a surge of interest in generating 4D content.
Self-supervised Spatiotemporal Representation Learning by Exploiting Video Continuity
Recent self-supervised video representation learning methods have found significant success by exploring essential properties of videos, e. g. speed, temporal order, etc.
Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder
State of the art (SOTA) few-shot learning (FSL) methods suffer significant performance drop in the presence of domain differences between source and target datasets.
Stain Style Transfer of Histopathology Images Via Structure-Preserved Generative Learning
To address the issue of color variations in histopathology images, this study proposes two stain style transfer models, SSIM-GAN and DSCSI-GAN, based on the generative adversarial networks.
New Interpretations of Normalization Methods in Deep Learning
In recent years, a variety of normalization methods have been proposed to help train neural networks, such as batch normalization (BN), layer normalization (LN), weight normalization (WN), group normalization (GN), etc.
DARTS+: Improved Differentiable Architecture Search with Early Stopping
Therefore, we propose a simple and effective algorithm, named "DARTS+", to avoid the collapse and improve the original DARTS, by "early stopping" the search procedure when meeting a certain criterion.
