Dataset Condensation aims to condense a large dataset into a smaller one...
In this paper, we introduce a realistic and challenging domain adaptatio...
In this paper, we address a complex but practical scenario in semi-super...
Audio-driven facial reenactment is a crucial technique that has a range ...
In this paper, we follow a data-centric philosophy and propose a novel m...
In-betweening is a technique for generating transitions given initial an...
Many dense 3D point clouds have been exploited to represent visual objec...
Restricted by the limited interaction area of native AR glasses (e.g., t...
Deep models trained with noisy labels are prone to over-fitting and stru...
Despite the extensive studies on Generative Adversarial Networks (GANs),...
Semi-supervised domain adaptation (SSDA) aims to apply knowledge learned...
A key challenge of blind image super resolution is to recover realistic
...
We present PVSeRF, a learning framework that reconstructs neural radianc...
StyleGAN is able to produce photorealistic images that are almost
indist...
Numerical computation of shortest paths or geodesics on curved domains, ...
We propose semantic region-adaptive normalization (SEAN), a simple but
e...
We propose Image2StyleGAN++, a flexible image editing framework with man...
We propose an efficient algorithm to embed a given image into the latent...
In this paper, we address the recent controversy between Lipschitz
regul...