Learning Multi-Object Tracking and Segmentation From Automatic Annotations
Lorenzo Porzi, Markus Hofinger, Idoia Ruiz, Joan Serrat, Samuel Rota Bulò, Peter Kontschieder
2020年份
10顶会引用
摘要
es * Figure 1: KITTI sub-sequences with automatically generated MOTS annotations as color-coded instance masks (left to right).
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引用它的顶会 Paper10
- TrackFormer: Multi-Object Tracking with TransformersTim Meinhardt, Alexander Kirillov, Laura Leal-Taixé, Christoph FeichtenhoferCVPR 2022 · 被引用 927 次
- Video K-Net: A Simple, Strong, and Unified Baseline for Video SegmentationXiangtai Li, Wenwei Zhang, Jiangmiao Pang, Kai Chen 等CVPR 2022 · 被引用 71 次
- RPEFlow: Multimodal Fusion of RGB-PointCloud-Event for Joint Optical Flow and Scene Flow EstimationZhexiong Wan, Yuxin Mao, Jing Zhang, Yuchao DaiICCV 2023 · 被引用 35 次
- Tube-Link: A Flexible Cross Tube Framework for Universal Video SegmentationXiangtai Li, Haobo Yuan, Wenwei Zhang, Guangliang Cheng 等ICCV 2023 · 被引用 29 次
- Continuous Copy-Paste for One-stage Multi-object Tracking and SegmentationZhenbo Xu, Ajin Meng, Zhenbo Shi, Wei Yang 等ICCV 2021 · 被引用 21 次
它引用的顶会 Paper2
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