We present a single network method for panoptic segmentation. This method combines the
predictions from a jointly trained semantic and instance segmentation network using …

In this work, we introduce the new scene understanding task of Part-aware Panoptic Segmentation
(PPS), which aims to understand a scene at multiple levels of abstraction, and unifies …

This paper introduces Content-aware Token Sharing (CTS), a token reduction approach that
improves the computational efficiency of semantic segmentation networks that use Vision …

For autonomous vehicles and mobile robots to safely operate in the real world, ie, the wild,
scene understanding models should perform well in the many different scenarios that can be …

Unified panoptic segmentation methods are achieving state-of-the-art results on several
datasets. To achieve these results on high-resolution datasets, these methods apply crop-based …

In this technical report, we present two novel datasets for image scene understanding. Both
datasets have annotations compatible with panoptic segmentation and additionally they …

Part-aware panoptic segmentation (PPS) requires (a) that each foreground object and
background region in an image is segmented and classified and (b) that all parts within …

In this work, we present an end-to-end network for fast panoptic segmentation. This network,
called Fast Panoptic Segmentation Network (FPSNet), does not require computationally …

In this work, we propose a single deep neural network for panoptic segmentation, for which
the goal is to provide each individual pixel of an input image with a class label, as in …

Recent work showed that large diffusion models can be reused as highly precise monocular
depth estimators by casting depth estimation as an image-conditional image generation task…