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Found 7 papers, 4 papers with code
Frequency Decomposition to Tap the Potential of Single Domain for Generalization
Then, a new method that learns through multiple frequency domains is proposed.
CLIPER: A Unified Vision-Language Framework for In-the-Wild Facial Expression Recognition
Facial expression recognition (FER) is an essential task for understanding human behaviors.
Dynamic Facial Expression Recognition
Facial Expression Recognition
+1
Domain-Unified Prompt Representations for Source-Free Domain Generalization
The proposed scheme generates diverse prompts from a domain bank that contains many more diverse domains than existing DG datasets.
Intensity-Aware Loss for Dynamic Facial Expression Recognition in the Wild
One of the main reasons is that video sequences often contain frames with different expression intensities, especially for the facial expressions in the real-world scenarios, while the images in SFER frequently present uniform and high expression intensities.
Ranked #8 on
Dynamic Facial Expression Recognition
on FERV39k
Dynamic Facial Expression Recognition
Facial Expression Recognition
+1
Enhancing Backdoor Attacks with Multi-Level MMD Regularization
Then, ML-MMDR, a difference reduction method that adds multi-level MMD regularization into the loss, is proposed, and its effectiveness is testified on three typical difference-based defense methods.
A New Perspective on Stabilizing GANs training: Direct Adversarial Training
Quite a number of methods have been proposed to stabilize the training of GANs, the focuses of which were respectively put on the loss functions, regularization and normalization technologies, training algorithms, and model architectures.
Interpreting the Latent Space of GANs via Correlation Analysis for Controllable Concept Manipulation
Generative adversarial nets (GANs) have been successfully applied in many fields like image generation, inpainting, super-resolution and drug discovery, etc., by now, the inner process of GANs is far from been understood.
