Existing computer vision systems can compete with humans in understanding the visible
parts of objects, but still fall far short of humans when it comes to depicting the invisible parts …

This paper studies amodal image segmentation: predicting entire object segmentation
masks including both visible and invisible (occluded) parts. In previous work the amodal …

Although current computer vision systems are closer to the human intelligence when it
comes to comprehending the visible world than previously, their performance is hindered …

Text-to-image generation has achieved astonishing results yet precise spatial controllability
and prompt fidelity remain highly challenging. This limitation is typically addressed through …

Deoccluding the hidden portions of objects in a scene is a formidable task, particularly when
addressing real-world scenes. In this paper, we present a new self-supervised PArallel …

We introduce PICFormer, a novel framework for P luralistic I mage C ompletion using a trans
Former based architecture, that achieves both high quality and diversity at a much faster …

In this work, we present SynTable, a unified and flexible Python-based dataset generator
built using NVIDIA's Isaac Sim Replicator Composer for generating high-quality synthetic …

Amodal scene analysis entails interpreting the occlusion relationship among scene
elements and inferring the possible shapes of the invisible parts. Existing methods typically …

Common object detection and image segmentation methods are unable to accurately
estimate the shape of the occluded fruit. Monitoring the growth status of shaded crops in a …

Equipment failures and communication interruptions of satellites, aircraft and ground
devices lead to data loss in Space-Air-Ground Integrated Internet of Things (SAGIoT). The …