In this article, we propose a software-driven drift detection and calibration framework based on probabilistic observation in latent space using variational autoencoders (VAEs). The proposed method ...

EdgeConnect+: Adversarial Inpainting with Edge and Color Guidance A deep learning-based image inpainting framework that integrates edge and color guidance to enhance image restoration. Suitable for ...

The image is first encoded by a variational autoencoder (VAE) into a lower-dimensional latent space. The latent image is then divided into a grid of patches, & each patch is flattened into a vector.

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the model uses a pretrained 3D variational autoencoder to encode both the input video and the reference image. These latents are patchified, concatenated, and fed into the DiT, which processes them ...

We also employ a variational autoencoder to reconstruct latent representations of non-imaging features aligned with imaging features. Based on this, we introduce Adaptive Cross-Modal Graph Learning ...