YouTube-VOS 2018 (Youtube Video Object Segmentation)
Introduced by Ning Xu et al. in YouTube-VOS: A Large-Scale Video Object Segmentation Benchmark
Youtube-VOS is a Video Object Segmentation dataset that contains 4,453 videos - 3,471 for training, 474 for validation, and 508 for testing. The training and validation videos have pixel-level ground truth annotations for every 5th frame (6 fps). It also contains Instance Segmentation annotations. It has more than 7,800 unique objects, 190k high-quality manual annotations and more than 340 minutes in duration.
Source: CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule RoutingBenchmarks
| Trend | Task | Dataset Variant | Best Model | Paper | Code |
|---|---|---|---|---|---|
|
YouTube-VOS 2018
|
Cutie+
|
|||
|
YouTube-VOS 2019
|
Cutie+
|
|||
|
YouTube-VOS 2018
|
XMem
|
|||
|
YouTube-VOS 2019
|
XMem
|
|||
|
YouTube-VOS 2018
|
ProPainter
|
|||
|
YouTube-VOS 2018
|
OSVOS
|
|||
|
YouTube-VOS
|
FGT++
|
|||
|
YouTube-VOS 2018
|
RVOS-Mask-ST+
|
|||
|
YouTube-VOS
|
AOC-MF
|
|||
|
YouTube-VOS
|
RVOS-Mask-ST+
|
Papers
| Paper | Code | Results | Date | Stars |
|---|
Dataset Loaders
No data loaders found. You can
submit your data loader here.
No data loaders found. You can
submit your data loader here.
