When performing remote sensing image segmentation, practitioners often encounter various
challenges, such as a strong imbalance in the foreground–background, the presence of tiny …

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

Temporal action detection (TAD) involves the localization and classification of action
instances within untrimmed videos. While standard TAD follows fully supervised learning …

Amodal object segmentation is a challenging task that involves segmenting both visible and
occluded parts of an object. In this paper, we propose a novel approach, called Coarse-to …

Amodal instance segmentation (AIS) predicts the complete shape of the occluded object,
including both visible and occluded regions. Because visual clues are lacking, the occluded …

High-throughput acquisition of phenotypic parameters based on machine vision is important
for intelligent breeding, digital cultivation and automated harvesting of Oudemansiella …

Perceiving the complete shape of occluded objects is essential for human and machine
intelligence. While the amodal segmentation task is to predict the complete mask of partially …

Unlike humans, who can effortlessly estimate the entirety of objects even when partially
occluded, modern computer vision algorithms still find this aspect extremely challenging …

In the food industry, assessing the quality of poultry carcasses during processing is a crucial
step. This study proposes an effective approach for automating the assessment of carcass …

Our work aims to reconstruct a 3D object that is held and rotated by a hand in front of a static
RGB camera. Previous methods that use implicit neural representations to recover the …