Panoptic Image Annotation with a Collaborative Assistant
Abstract
This paper aims to reduce the time to annotate images for panoptic
segmentation, which requires annotating segmentation masks and
class labels for all object instances and stuff regions. We formulate
our approach as a collaborative process between an annotator
and an automated assistant who take turns to jointly annotate an
image using a predefined pool of segments. Actions performed by
the annotator serve as a strong contextual signal. The assistant
intelligently reacts to this signal by annotating other parts of the
image on its own, which reduces the amount of work required by
the annotator. We perform thorough experiments on the COCO
panoptic dataset, both in simulation and with human annotators.
These demonstrate that our approach is significantly faster than
the recent machine-assisted interface of [4], and 2.4x to 5x faster
than manual polygon drawing. Finally, we show on ADE20k [62]
that our method can be used to efficiently annotate new datasets,
bootstrapping from a very small amount of annotated data.
segmentation, which requires annotating segmentation masks and
class labels for all object instances and stuff regions. We formulate
our approach as a collaborative process between an annotator
and an automated assistant who take turns to jointly annotate an
image using a predefined pool of segments. Actions performed by
the annotator serve as a strong contextual signal. The assistant
intelligently reacts to this signal by annotating other parts of the
image on its own, which reduces the amount of work required by
the annotator. We perform thorough experiments on the COCO
panoptic dataset, both in simulation and with human annotators.
These demonstrate that our approach is significantly faster than
the recent machine-assisted interface of [4], and 2.4x to 5x faster
than manual polygon drawing. Finally, we show on ADE20k [62]
that our method can be used to efficiently annotate new datasets,
bootstrapping from a very small amount of annotated data.
Research Areas
