Image inpainting is an important research direction in the study of computer vision, and is
widely used in image editing and photo inpainting etc. Traditional image inpainting …

We survey recent work on neurosymbolic programming, an emerging area that bridges the
areas of deep learning and program synthesis. Like in classic machine learning, the goal …

Recently there has been an interest in the potential of learning generative models from a
single image, as opposed to from a large dataset. This task is of significance, as it means …

In this paper, we focus on semantically multi-modal image synthesis (SMIS) task, namely,
generating multi-modal images at the semantic level. Previous work seeks to use multiple …

Programming-by-Examples (PBE) aims to generate an algorithm from input-output
examples. Such systems are practically and theoretically important: from an end-user …

Human activity understanding is of widespread interest in artificial intelligence and spans
diverse applications like health care and behavior analysis. Although there have been …

Programs, consisting of semantic and structural information, play an important role in the
communication between humans and agents. Towards learning general program executors …

Shape programs encode shape structures by representing object parts as subroutines and
constructing the overall shape by composing these subroutines. This usually involves the …

n recent years, text-guided image manipulation has gained increasing attention in the
multimedia and computer vision community. The input to conditional image generation has …

We introduce Cosmos, a framework for object-centric world modeling that is designed for
compositional generalization (CompGen), ie, high performance on unseen input scenes …