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Found 9 papers, 4 papers with code
Enhancing Molecular Property Prediction via Mixture of Collaborative Experts
To address data scarcity and imbalance in MPP, some studies have adopted Graph Neural Networks (GNN) as an encoder to extract commonalities from molecular graphs.
Video Coding Using Learned Latent GAN Compression
We leverage the generative capacity of GANs such as StyleGAN to represent and compress a video, including intra and inter compression.
Semantic Unfolding of StyleGAN Latent Space
Generative adversarial networks (GANs) have proven to be surprisingly efficient for image editing by inverting and manipulating the latent code corresponding to an input real image.
Feature-Style Encoder for Style-Based GAN Inversion
Additionally, we demonstrate that the proposed encoder is especially well-suited for inversion and editing on videos.
Learning Perceptual Compression of Facial Video
We leverage the generative capacity of GANs such as StyleGAN to represent and compress each video frame (intra compression), as well as the successive differences between frames (inter compression).
Semantic and Geometric Unfolding of StyleGAN Latent Space
Generative adversarial networks (GANs) have proven to be surprisingly efficient for image editing by inverting and manipulating the latent code corresponding to a natural image.
A Latent Transformer for Disentangled Face Editing in Images and Videos
Previous works that attempt to tackle this problem may suffer from the entanglement of facial attributes and the loss of the person's identity.
Photo style transfer with consistency losses
We address the problem of style transfer between two photos and propose a new way to preserve photorealism.
