Object detection or localization is an incremental step in progression from coarse to fine
digital image inference. It not only provides the classes of the image objects, but also …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO
series and is easily extensible for many object recognition tasks such as instance …

Open-vocabulary segmentation is a challenging task requiring segmenting and recognizing
objects from an open set of categories in diverse environments. One way to address this …

Image segmentation groups pixels with different semantics, eg, category or instance
membership. Each choice of semantics defines a task. While only the semantics of each task …

We present a new method for efficient high-quality image segmentation of objects and
scenes. By analogizing classical computer graphics methods for efficient rendering with over …

In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast system for panoptic
segmentation, aiming to establish a solid baseline for bottom-up methods that can achieve …

We present a simple, fully-convolutional model for real-time instance segmentation that
achieves 29.8 mAP on MS COCO at 33.5 fps evaluated on a single Titan Xp, which is …

The recently introduced panoptic segmentation task has renewed our community's interest
in unifying the tasks of instance segmentation (for thing classes) and semantic segmentation …

Letting a deep network be aware of the quality of its own predictions is an interesting yet
important problem. In the task of instance segmentation, the confidence of instance …