Partial convolution weights convolutions with binary masks and renormalizes on valid pixels.
It was originally proposed for image inpainting task because a corrupted image processed …

We propose VecGAN, an image-to-image translation framework for facial attribute editing
with interpretable latent directions. Facial attribute editing task faces the challenges of …

Abstract Generative Adversarial Networks (GANs) produce impressive results on
unconditional image generation when powered with large-scale image datasets. Yet …

We propose a learning-based method to recover normals, specularity, and roughness from a
single diffuse image of a material, using microgeometry appearance as our primary cue …

CNN's limited receptive field restricts its ability to capture long-range spatial-temporal
dependencies, leading to unsatisfactory performance in video super-resolution. To tackle …

Image harmonization aims to produce visually harmonious composite images by adjusting
the foreground appearance to be compatible with the background. When the composite …

Texture recognition is a challenging visual task since its multiple primitives or attributes can
be perceived from the texture image under different spatial contexts. Existing approaches …

Humans can easily infer the underlying 3D geometry and texture of an object only from a
single 2D image. Current computer vision methods can do this, too, but suffer from view …

This paper presents a method to achieve fine detailed texture learning for 3D models that
are reconstructed from both multi-view and single-view images. The framework is posed as …

Real-time graphics applications require high-quality textured materials to convey realism in
virtual environments. Generating these textures is challenging as they need to be visually …