paper-with-me

Semi-Supervised Video Object Segmentation 벤치마크

Semi-Supervised Video Object Segmentation on DAVIS 2016

234개 결과 · ⬇ CSV · JSON

J&F

53.8 63.7 73.6 83.5 93.4 2015-12 2026-09 FCP — 53.8 (2015-12-01) FCP — 53.8 (2015-12-01) FCP — 53.8 (2015-12-01) OFL — 65.7 (2016-06-01) BVS — 59.4 (2016-06-01) OFL — 65.7 (2016-06-01) BVS — 59.4 (2016-06-01) OFL — 65.7 (2016-06-01) BVS — 59.4 (2016-06-01) OSVOS — 80.2 (2016-11-16) OSVOS — 80.2 (2016-11-16) OSVOS — 80.2 (2016-11-16) MSK — 77.55 (2016-12-08) MSK — 77.55 (2016-12-08) MSK — 77.55 (2016-12-08) VPN — 67.9 (2016-12-16) VPN — 67.9 (2016-12-16) VPN — 67.9 (2016-12-16) Lucid — 82.95 (2017-03-28) Lucid — 82.95 (2017-03-28) Lucid — 82.95 (2017-03-28) OnAVOS — 85.5 (2017-06-28) OnAVOS — 85.5 (2017-06-28) OnAVOS — 85.5 (2017-06-28) CTN — 71.4 (2017-07-01) CTN — 71.4 (2017-07-01) CTN — 71.4 (2017-07-01) PLM — 66.35 (2017-08-17) PLM — 66.35 (2017-08-17) PLM — 66.35 (2017-08-17) OSVOS-S — 86.55 (2017-09-18) OSVOS-S — 86.55 (2017-09-18) OSVOS-S — 86.55 (2017-09-18) SFL — 76.05 (2017-09-20) SFL — 76.05 (2017-09-20) SFL — 76.05 (2017-09-20) OSMN — 73.45 (2018-02-04) OSMN — 73.45 (2018-02-04) OSMN — 73.45 (2018-02-04) VOSwL — 83.65 (2018-03-21) VOSwL — 83.65 (2018-03-21) VOSwL — 83.65 (2018-03-21) CINM — 84.2 (2018-03-26) CINM — 84.2 (2018-03-26) CINM — 84.2 (2018-03-26) PML — 77.4 (2018-04-09) PML — 77.4 (2018-04-09) PML — 77.4 (2018-04-09) RGMP — 81.75 (2018-06-01) RGMP — 81.75 (2018-06-01) RGMP — 81.75 (2018-06-01) FAVOS — 80.95 (2018-06-06) FAVOS — 80.95 (2018-06-06) FAVOS — 80.95 (2018-06-06) PReMVOS — 86.75 (2018-07-24) PReMVOS — 86.75 (2018-07-24) PReMVOS — 86.75 (2018-07-24) AGAME — 81.85 (2018-11-28) AGAME — 81.85 (2018-11-28) AGAME — 81.85 (2018-11-28) SiamMask — 69.75 (2018-12-12) SiamMask — 69.75 (2018-12-12) SiamMask — 69.75 (2018-12-12) FEELVOS — 81.65 (2019-02-25) FEELVOS — 81.65 (2019-02-25) FEELVOS — 81.65 (2019-02-25) STM — 89.4 (2019-04-01) STM — 89.4 (2019-04-01) STM — 89.4 (2019-04-01) Spatiotemporal CNN — 83.8 (2019-04-04) Spatiotemporal CNN — 83.8 (2019-04-04) Spatiotemporal CNN — 83.8 (2019-04-04) MHP-VOS — 88.55 (2019-04-17) MHP-VOS — 88.55 (2019-04-17) MHP-VOS — 88.55 (2019-04-17) Hou et al. — 77.75 (2019-07-21) Hou et al. — 77.75 (2019-07-21) Hou et al. — 77.75 (2019-07-21) RANet+ (online learning) — 87.1 (2019-08-19) RANet — 85.45 (2019-08-19) RANet+ (online learning) — 87.1 (2019-08-19) RANet — 85.45 (2019-08-19) RANet+ (online learning) — 87.1 (2019-08-19) RANet — 85.45 (2019-08-19) Siam R-CNN — 78.6 (2019-11-28) Siam R-CNN — 78.6 (2019-11-28) Siam R-CNN — 78.6 (2019-11-28) CRVOS — 81.6 (2020-02-10) CRVOS — 81.6 (2020-02-10) CRVOS — 81.6 (2020-02-10) FRTM (val) — 81.7 (2020-02-27) FRTM (val) — 81.7 (2020-02-27) FRTM (val) — 81.7 (2020-02-27) MuG-W — 64.65 (2020-03-10) MuG-W — 64.65 (2020-03-10) MuG-W — 64.65 (2020-03-10) CFBI — 89.4 (2020-03-18) CFBI — 89.4 (2020-03-18) CFBI — 89.4 (2020-03-18) RGMP (val) — 68.8 (2020-07-11) RGMP (val) — 68.8 (2020-07-11) RGMP (val) — 68.8 (2020-07-11) KMN — 90.5 (2020-07-16) KMN — 90.5 (2020-07-16) KMN — 90.5 (2020-07-16) LSMVOS — 86.5 (2020-09-02) LSMVOS — 86.5 (2020-09-02) LSMVOS — 86.5 (2020-09-02) CFBI+ — 89.9 (2020-10-13) CFBI+ — 89.9 (2020-10-13) CFBI+ — 89.9 (2020-10-13) e-OSVOS — 86.8 (2020-12-03) e-OSVOS — 86.8 (2020-12-03) e-OSVOS — 86.8 (2020-12-03) SSM-VOS — 85.9 (2021-02-18) SSM-VOS — 85.9 (2021-02-18) SSM-VOS — 85.9 (2021-02-18) MiVOS — 91.0 (2021-03-14) MiVOS — 91.0 (2021-03-14) MiVOS — 91.0 (2021-03-14) RMNet — 88.8 (2021-03-24) RMNet — 88.8 (2021-03-24) RMNet — 88.8 (2021-03-24) SwinB-AOT-L — 92.0 (2021-06-04) R50-AOT-L — 91.1 (2021-06-04) AOT-L — 90.4 (2021-06-04) AOT-L — 89.9 (2021-06-04) AOT-S — 89.4 (2021-06-04) AOT-T — 86.8 (2021-06-04) SwinB-AOT-L — 92.0 (2021-06-04) R50-AOT-L — 91.1 (2021-06-04) AOT-L — 90.4 (2021-06-04) AOT-L — 89.9 (2021-06-04) AOT-S — 89.4 (2021-06-04) AOT-T — 86.8 (2021-06-04) SwinB-AOT-L — 92.0 (2021-06-04) R50-AOT-L — 91.1 (2021-06-04) AOT-L — 90.4 (2021-06-04) AOT-L — 89.9 (2021-06-04) AOT-S — 89.4 (2021-06-04) AOT-T — 86.8 (2021-06-04) STCN — 91.7 (2021-06-09) STCN — 91.7 (2021-06-09) STCN — 91.7 (2021-06-09) HMMN — 90.8 (2021-09-23) HMMN — 90.8 (2021-09-23) HMMN — 90.8 (2021-09-23) RPCMVOS — 90.6 (2021-12-06) RPCMVOS — 90.6 (2021-12-06) RPCMVOS — 90.6 (2021-12-06) SwinB-AOTv2-L (MS) — 93.0 (2022-03-22) SwinB-AOST (L'=3, MS) — 93.0 (2022-03-22) SwinB-AOTv2-L — 92.4 (2022-03-22) SwinB-AOST (L'=3) — 92.4 (2022-03-22) R50-AOST (L'=3) — 92.1 (2022-03-22) R50-AOST (L'=2) — 92.0 (2022-03-22) R50-AOST (L'=1) — 90.3 (2022-03-22) SwinB-AOTv2-L (MS) — 93.0 (2022-03-22) SwinB-AOST (L'=3, MS) — 93.0 (2022-03-22) SwinB-AOTv2-L — 92.4 (2022-03-22) SwinB-AOST (L'=3) — 92.4 (2022-03-22) R50-AOST (L'=3) — 92.1 (2022-03-22) R50-AOST (L'=2) — 92.0 (2022-03-22) R50-AOST (L'=1) — 90.3 (2022-03-22) SwinB-AOTv2-L (MS) — 93.0 (2022-03-22) SwinB-AOST (L'=3, MS) — 93.0 (2022-03-22) SwinB-AOTv2-L — 92.4 (2022-03-22) SwinB-AOST (L'=3) — 92.4 (2022-03-22) R50-AOST (L'=3) — 92.1 (2022-03-22) R50-AOST (L'=2) — 92.0 (2022-03-22) R50-AOST (L'=1) — 90.3 (2022-03-22) XMem (BL30K, MS) — 93.3 (2022-07-14) XMem (MS) — 92.7 (2022-07-14) XMem (BL30K) — 92.0 (2022-07-14) XMem — 91.5 (2022-07-14) XMem (DAVIS+YouTubeVOS only) — 90.8 (2022-07-14) XMem (DAVIS only) — 87.8 (2022-07-14) XMem (BL30K, MS) — 93.3 (2022-07-14) XMem (MS) — 92.7 (2022-07-14) XMem (BL30K) — 92.0 (2022-07-14) XMem — 91.5 (2022-07-14) XMem (DAVIS+YouTubeVOS only) — 90.8 (2022-07-14) XMem (DAVIS only) — 87.8 (2022-07-14) XMem (BL30K, MS) — 93.3 (2022-07-14) XMem (MS) — 92.7 (2022-07-14) XMem (BL30K) — 92.0 (2022-07-14) XMem — 91.5 (2022-07-14) XMem (DAVIS+YouTubeVOS only) — 90.8 (2022-07-14) XMem (DAVIS only) — 87.8 (2022-07-14) QDMN — 92.0 (2022-07-16) QDMN — 92.0 (2022-07-16) QDMN — 92.0 (2022-07-16) RAVOS — 91.7 (2022-07-21) RAVOS — 91.7 (2022-07-21) RAVOS — 91.7 (2022-07-21) SWEM (val) — 88.1 (2022-08-22) SWEM (val) — 88.1 (2022-08-22) SWEM (val) — 88.1 (2022-08-22) SwinB-DeAOT-L — 92.9 (2022-10-18) R50-DeAOT-L — 92.3 (2022-10-18) DeAOT-L — 92.0 (2022-10-18) DeAOT-B — 91.0 (2022-10-18) DeAOT-S — 89.3 (2022-10-18) DeAOT-T — 88.9 (2022-10-18) SwinB-DeAOT-L — 92.9 (2022-10-18) R50-DeAOT-L — 92.3 (2022-10-18) DeAOT-L — 92.0 (2022-10-18) DeAOT-B — 91.0 (2022-10-18) DeAOT-S — 89.3 (2022-10-18) DeAOT-T — 88.9 (2022-10-18) SwinB-DeAOT-L — 92.9 (2022-10-18) R50-DeAOT-L — 92.3 (2022-10-18) DeAOT-L — 92.0 (2022-10-18) DeAOT-B — 91.0 (2022-10-18) DeAOT-S — 89.3 (2022-10-18) DeAOT-T — 88.9 (2022-10-18) ISVOS (BL30K, MS) — 93.4 (2022-12-13) ISVOS (BL30K, MS) — 93.4 (2022-12-13) ISVOS (BL30K, MS) — 93.4 (2022-12-13) MobileVOS (BL30K) — 91.4 (2023-03-14) MobileVOS — 90.6 (2023-03-14) MobileVOS (BL30K) — 91.4 (2023-03-14) MobileVOS — 90.6 (2023-03-14) MobileVOS (BL30K) — 91.4 (2023-03-14) MobileVOS — 90.6 (2023-03-14) STCN + TrickVOS (PT) — 91.8 (2023-06-27) Lightweight TrickVOS (PT) — 89.3 (2023-06-27) STCN + TrickVOS (PT) — 91.8 (2023-06-27) Lightweight TrickVOS (PT) — 89.3 (2023-06-27) STCN + TrickVOS (PT) — 91.8 (2023-06-27) Lightweight TrickVOS (PT) — 89.3 (2023-06-27) FCP — 53.8 (2015-12-01) OFL — 65.7 (2016-06-01) OSVOS — 80.2 (2016-11-16) Lucid — 82.95 (2017-03-28) OnAVOS — 85.5 (2017-06-28) OSVOS-S — 86.55 (2017-09-18) PReMVOS — 86.75 (2018-07-24) STM — 89.4 (2019-04-01) KMN — 90.5 (2020-07-16) MiVOS — 91.0 (2021-03-14) SwinB-AOT-L — 92.0 (2021-06-04) SwinB-AOTv2-L (MS) — 93.0 (2022-03-22) XMem (BL30K, MS) — 93.3 (2022-07-14) ISVOS (BL30K, MS) — 93.4 (2022-12-13)
RankModel J&FJaccard (Mean)Jaccard (Recall)Jaccard (Decay)F-measure (Mean)F-measure (Recall)F-measure (Decay)Speed (FPS) Extra Training Data PaperCodeYear
1 ISVOS (BL30K, MS) 93.492.5––94.2––– ✓ Look Before You Match: Instance Understanding Matters in Video Object Segmentation 2022
2 XMem (BL30K, MS) 93.392.2––94.4––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
3 SwinB-AOTv2-L (MS) 93.091.6––94.4––1.3 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
3 SwinB-AOST (L'=3, MS) 93.091.5––94.5––1.3 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
5 SwinB-DeAOT-L 92.991.1––94.7––15.4 Decoupling Features in Hierarchical Propagation for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2022
6 XMem (MS) 92.792.0––93.5––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
7 SwinB-AOTv2-L 92.490.6––94.1––12.0 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
7 SwinB-AOST (L'=3) 92.490.5––94.2––12.0 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
9 R50-DeAOT-L 92.390.5––94.0––27.0 Decoupling Features in Hierarchical Propagation for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2022
10 R50-AOST (L'=3) 92.190.6––93.6––17.5 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
11 SwinB-AOT-L 92.090.7––93.3––12.1 Associating Objects with Transformers for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2021
11 XMem (BL30K) 92.090.7––93.2––29.6 ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
11 QDMN 92.090.7––93.2––– ✓ Learning Quality-aware Dynamic Memory for Video Object Segmentation workforai/qdmn 2022
11 R50-AOST (L'=2) 92.090.5––93.4––24.3 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
11 DeAOT-L 92.090.3––93.7––28.5 Decoupling Features in Hierarchical Propagation for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2022
16 STCN + TrickVOS (PT) 91.890.5––93.1––– TrickVOS: A Bag of Tricks for Video Object Segmentation 2023
17 RAVOS 91.790.8––92.6––58 ✓ Region Aware Video Object Segmentation with Deep Motion Modeling 2022
17 STCN 91.790.498.14.193.097.14.326.9 ✓ Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation hkchengrex/STCN · limingxing00/rde-vos-cvpr2022 · alipga/AMM_VOS 2021
19 XMem 91.590.4––92.7––29.6 ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
20 MobileVOS (BL30K) 91.490.3––92.6––100.1 ✓ MobileVOS: Real-Time Video Object Segmentation Contrastive Learning meets Knowledge Distillation 2023
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