WayPOP: A Panoramic Open-Set Panoptic Tracking Benchmark
Overview
This research introduces WayPOP, a new benchmark for panoramic open-set panoptic tracking. Built on real Waymo PVPS sequences augmented with diverse out-of-taxonomy 3D assets from Objaverse, the dataset provides temporally and cross-view consistent annotations for unknown objects. It contains approximately 670 curated assets instantiated as 980 unique unknown-object tracks, yielding 53,452 mask annotations across 21,300 camera images. The authors evaluate representative open-set and open-vocabulary segmentation methods, revealing substantial limitations in current approaches for robust unknown-object localization and identity association across time and views.
Generated from attributed reports · Updated 3 days ago
Event evidence and corrections
0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.
Reported quantity · camera images: 21300 other · Basis not reported
“nd surrounding traffic move, providing temporally and cross-view consistent panoptic annotations and auxiliary LiDAR range observations. WayPOP contains approximately 670 curated assets instantiated as 980 unique unknown-object tracks, yielding 53,452 unknown-object mask annotations across 21,300 camera images. Our evaluation protocol defines a hierarchy of tasks from view-independent open-set panoptic segmentation t”
Exact source · revision 1Source owner not reported
Reported quantity · unknown-object tracks: 980 other · Basis not reported
“nd surrounding traffic move, providing temporally and cross-view consistent panoptic annotations and auxiliary LiDAR range observations. WayPOP contains approximately 670 curated assets instantiated as 980 unique unknown-object tracks, yielding 53,452 unknown-object mask annotations across 21,300 camera images. Our evaluation protocol defines a hierarchy of tasks from view-independent open-set panoptic segmentation t”
Exact source · revision 1Source owner not reported
Reported quantity · unknown-object mask annotations: 53452 other · Basis not reported
“nd surrounding traffic move, providing temporally and cross-view consistent panoptic annotations and auxiliary LiDAR range observations. WayPOP contains approximately 670 curated assets instantiated as 980 unique unknown-object tracks, yielding 53,452 unknown-object mask annotations across 21,300 camera images. Our evaluation protocol defines a hierarchy of tasks from view-independent open-set panoptic segmentation t”
Exact source · revision 1Source owner not reported
Reported quantity · curated assets: 670 other · Basis not reported
“nd surrounding traffic move, providing temporally and cross-view consistent panoptic annotations and auxiliary LiDAR range observations. WayPOP contains approximately 670 curated assets instantiated as 980 unique unknown-object tracks, yielding 53,452 unknown-object mask annotations across 21,300 camera images. Our evaluation protocol defines a hierarchy of tasks from view-independent open-set panoptic segmentation t”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsSignalWayPOP: A Panoramic Open-Set Panoptic Tracking Benchmark
This research introduces WayPOP, a new benchmark for panoramic open-set panoptic tracking. Built on real Waymo PVPS sequences augmented with diverse out-of-taxonomy 3D assets from Objaverse, the dataset provides temporally and cross-view consistent annotations for unknown objects. It contains approximately 670 curated assets instantiated as 980 unique unknown-object tracks, yielding 53,452 mask annotations across 21,300 camera images. The authors evaluate representative open-set and open-vocabulary segmentation methods, revealing substantial limitations in current approaches for robust unknown-object localization and identity association across time and views.
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