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Referring Video Object Segmentation On Mevis

Métriques

F

J

Ju0026F

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	F	J	Ju0026F	Paper Title	Repository
DsHmp + MTCM	51.1	44.1	47.6	Multi-Context Temporal Consistent Modeling for Referring Video Object Segmentation	-
HTR	45.5	39.9	42.7	Temporally Consistent Referring Video Object Segmentation with Hybrid Memory	-
VRS-HQ (Chat-UniVi-13B)	53.7	48	50.9	The Devil is in Temporal Token: High Quality Video Reasoning Segmentation	-
InternVideo2.5	-	-	32	InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling	-
MPG-SAM 2	56.7	50.7	53.7	MPG-SAM 2: Adapting SAM 2 with Mask Priors and Global Context for Referring Video Object Segmentation	-
ReferFormer	32.2	29.8	31.0	Language as Queries for Referring Video Object Segmentation	-
DsHmp	49.8	43	46.4	Decoupling Static and Hierarchical Motion Perception for Referring Video Segmentation	-
SAMWISE	51.2	45.4	48.3	SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation	-
LBDT	30.8	27.8	29.3	Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation	-
VLT+TC	37.3	33.6	35.5	VLT: Vision-Language Transformer and Query Generation for Referring Segmentation	-
LMPM	40.2	34.2	37.2	MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressions	-
MTTR	31.2	28.8	30.0	End-to-End Referring Video Object Segmentation with Multimodal Transformers	-
URVOS	29.9	25.7	27.8	URVOS: Unified Referring Video Object Segmentation Network with a Large-Scale Benchmark
ReferDINO (Swin-B)	53.9	44.7	49.3	ReferDINO: Referring Video Object Segmentation with Visual Grounding Foundations	-
FindTrack	50.7	45.6	48.2	Find First, Track Next: Decoupling Identification and Propagation in Referring Video Object Segmentation	-

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