Abstract Language-guided image inpainting aims to fill the defective regions of an image
under the guidance of text while keeping the non-defective regions unchanged. However …

Multimodal Conditional Image Synthesis (MCIS) aims to generate images according to
different modalities input and their combination, which allows users to describe their …

The task of Few-shot Learning (FSL) aims to do the inference on novel categories containing
only few labeled examples, with the help of knowledge learned from base categories …

Human motion transfer aims to transfer motions from a target dynamic person to a source
static one for motion synthesis. An accurate matching between the source person and the …

We present ASSET, a neural architecture for automatically modifying an input high-
resolution image according to a user's edits on its semantic segmentation map. Our …

Advances in computer vision are pushing the limits of im-age manipulation, with generative
models sampling detailed images on various tasks. However, a specialized model is often …

In order to get raw images of high quality for downstream Image Signal Process (ISP), in this
paper we present an Efficient Locally Multiplicative Transformer called ELMformer for raw …

Vision Transformers (ViTs) have attracted a lot of popularity in recent years, due to their
exceptional capabilities in modeling long-range spatial dependencies and scalability for …

This paper studies the task of conditional Human Motion Animation (cHMA). Given a source
image and a driving video, the model should animate the new frame sequence, in which the …

Reliable outlier detection is critical for real-world deployment of deep learning models.
Although extensively studied, likelihoods produced by deep generative models have been …