OVIS is a new large scale benchmark dataset for video instance segmentation task.
54 PAPERS • 1 BENCHMARK
3,859 high-resolution YouTube videos, 2,985 training videos, 421 validation videos and 453 test videos. An improved 40-category label set by merging eagle and owl into bird, ape into monkey, deleting hands, and adding flying disc, squirrel and whale 8,171 unique video instances 232k high-quality manual annotations
43 PAPERS • 1 BENCHMARK
UVO is a new benchmark for open-world class-agnostic object segmentation in videos.
22 PAPERS • 3 BENCHMARKS
BURST is a benchmark suite built upon TAO that requires tracking and segmenting multiple objects from camera video. Class-guided Common: Track and segment all objects belonging to a set of 78 common classes (based on the COCO class set) Long-tail: Track and segment all objects belonging to an extended set of 482 object all 482 object classes (class label predictions are not required) Exemplar-guided Mask: Track and segment all objects in the video for which the first-frame object masks are given. This task is identical to Video Object Segmentation (VOS). Box: Track and segment all objects in the video for which the first-frame object bounding-boxes are given. Point: Track and segment all objects in the video for which we are only given the (x,y) point coordinates of the mask centroid in the first-frame in which the objects appear.
14 PAPERS • 5 BENCHMARKS
YouTubeVIS is a new dataset tailored for tasks like simultaneous detection, segmentation and tracking of object instances in videos and is collected based on the current largest video object segmentation
145 PAPERS • 2 BENCHMARKS
Video object segmentation has been studied extensively in the past decade due to its importance in understanding video spatial-temporal structures as well as its value in industrial applications. Previously, we presented the first large-scale video object segmentation dataset named YouTubeVOS and hosted the Large-scale Video Object Segmentation Challenge in conjuction with ECCV 2018, ICCV 2019 This year, we are thrilled to invite you to the 4th Large-scale Video Object Segmentation Challenge in conjunction with CVPR 2022.
5 PAPERS • 1 BENCHMARK
While Video Instance Segmentation (VIS) has seen rapid progress, current approaches struggle to predict high-quality masks with accurate boundary details.
4 PAPERS • 1 BENCHMARK