Guided image synthesis enables everyday users to create and edit photo-realistic images
with minimum effort. The key challenge is balancing faithfulness to the user input (eg, hand …

Image completion has made tremendous progress with convolutional neural networks
(CNNs), because of their powerful texture modeling capacity. However, due to some …

Few-shot image generation (FSIG) aims to learn to generate new and diverse samples given
an extremely limited number of samples from a domain, eg, 10 training samples. Recent …

Free-form text prompts allow users to describe their intentions during image manipulation
conveniently. Based on the visual latent space of StyleGAN [21] and text embedding space …

GAN inversion and editing via StyleGAN maps an input image into the embedding spaces
(W, W^+, and F) to simultaneously maintain image fidelity and meaningful manipulation …

We propose SketchINR to advance the representation of vector sketches with implicit neural
models. A variable length vector sketch is compressed into a latent space of fixed dimension …

In this paper we explore the unique modality of sketch for explainability emphasising the
profound impact of human strokes compared to conventional pixel-oriented studies. Beyond …

Sketch-based image manipulation is an interactive image editing task to modify an image
based on input sketches from users. Existing methods typically convert this task into a …

We propose to restore old photos that suffer from severe degradation through a deep
learning approach. Unlike conventional restoration tasks that can be solved through …

Realistic 3D facial generation based on Neural Radiance Fields (NeRFs) from 2D sketches
benefits various applications. Despite the high realism of free-view rendering results of …