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Referring Video Object Segmentation On Ref

Metrics

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Results

Performance results of various models on this benchmark

Model Name
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Paper TitleRepository
FindTrack78.569.974.2Find First, Track Next: Decoupling Identification and Propagation in Referring Video Object Segmentation-
DsHmp68.161.764.9Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation-
SOC69.162.565.8SOC: Semantic-Assisted Object Cluster for Referring Video Object Segmentation-
URVOS56.047.351.6URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark
HTML65.159.262.1HTML: Hybrid Temporal-scale Multimodal Learning Framework for Referring Video Object Segmentation-
SgMg66.060.663.3Spectrum-guided Multi-granularity Referring Video Object Segmentation-
VD-IT72.666.269.4Exploring Pre-trained Text-to-Video Diffusion Models for Referring Video Object Segmentation-
MUTR71.364.868.0Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentation-
ReferFormer64.158.161.1Language as Queries for Referring Video Object Segmentation-
LoSh66.861.864.3LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation-
LBDT--54.5Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation-
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Referring Video Object Segmentation On Ref | SOTA | HyperAI