paper-with-me

Semi-Supervised Video Object Segmentation 벤치마크

Semi-Supervised Video Object Segmentation on DAVIS 2017 (test-dev)

177개 결과 · ⬇ CSV · JSON

J&F

41.3 53 64.7 76.4 88.1 2016-11 2026-11 OSVOS — 50.9 (2016-11-16) OSVOS — 50.9 (2016-11-16) OSVOS — 50.9 (2016-11-16) Lucid — 66.6 (2017-03-28) Lucid — 66.6 (2017-03-28) Lucid — 66.6 (2017-03-28) OnAVOS — 52.8 (2017-06-28) OnAVOS — 52.8 (2017-06-28) OnAVOS — 52.8 (2017-06-28) OSVOS-S — 57.5 (2017-09-18) OSVOS-S — 57.5 (2017-09-18) OSVOS-S — 57.5 (2017-09-18) OSMN — 41.3 (2018-02-04) OSMN — 41.3 (2018-02-04) OSMN — 41.3 (2018-02-04) CINM — 67.5 (2018-03-26) CINM — 67.5 (2018-03-26) CINM — 67.5 (2018-03-26) RGMP — 52.8 (2018-06-01) RGMP — 52.8 (2018-06-01) RGMP — 52.8 (2018-06-01) FAVOS — 43.6 (2018-06-06) FAVOS — 43.6 (2018-06-06) FAVOS — 43.6 (2018-06-06) PReMVOS — 71.6 (2018-07-24) PReMVOS — 71.6 (2018-07-24) PReMVOS — 71.6 (2018-07-24) AGAME — 52.3 (2018-11-28) AGAME — 52.3 (2018-11-28) AGAME — 52.3 (2018-11-28) SiamMask — 43.2 (2018-12-12) SiamMask — 43.2 (2018-12-12) SiamMask — 43.2 (2018-12-12) FEELVOS — 57.8 (2019-02-25) FEELVOS — 57.8 (2019-02-25) FEELVOS — 57.8 (2019-02-25) RVOS — 50.3 (2019-03-13) RVOS — 50.3 (2019-03-13) RVOS — 50.3 (2019-03-13) STM — 72.2 (2019-04-01) STM — 72.2 (2019-04-01) STM — 72.2 (2019-04-01) MHP-VOS — 69.5 (2019-04-17) MHP-VOS — 69.5 (2019-04-17) MHP-VOS — 69.5 (2019-04-17) RANet — 55.4 (2019-08-19) RANet — 55.4 (2019-08-19) RANet — 55.4 (2019-08-19) CapsuleVOS — 51.3 (2019-09-30) CapsuleVOS — 51.3 (2019-09-30) CapsuleVOS — 51.3 (2019-09-30) Siam R-CNN — 53.3 (2019-11-28) Siam R-CNN — 53.3 (2019-11-28) Siam R-CNN — 53.3 (2019-11-28) CFBI — 74.8 (2020-03-18) CFBI — 74.8 (2020-03-18) CFBI — 74.8 (2020-03-18) KMN — 77.2 (2020-07-16) KMN — 77.2 (2020-07-16) KMN — 77.2 (2020-07-16) LSMVOS — 67.4 (2020-09-02) LSMVOS — 67.4 (2020-09-02) LSMVOS — 67.4 (2020-09-02) CFBI+ — 78.0 (2020-10-13) CFBI+ — 78.0 (2020-10-13) CFBI+ — 78.0 (2020-10-13) e-OSVOS — 64.8 (2020-12-03) e-OSVOS — 64.8 (2020-12-03) e-OSVOS — 64.8 (2020-12-03) SSM-VOS — 62.0 (2021-02-18) SSM-VOS — 62.0 (2021-02-18) SSM-VOS — 62.0 (2021-02-18) MiVOS — 76.5 (2021-03-14) MiVOS — 76.5 (2021-03-14) MiVOS — 76.5 (2021-03-14) RMNet — 75.0 (2021-03-24) RMNet — 75.0 (2021-03-24) RMNet — 75.0 (2021-03-24) SwinB-AOT-L — 81.2 (2021-06-04) R50-AOT-L — 79.6 (2021-06-04) AOT-L — 78.3 (2021-06-04) AOT-B — 75.5 (2021-06-04) AOT-S — 73.9 (2021-06-04) AOT-T — 72.0 (2021-06-04) SwinB-AOT-L — 81.2 (2021-06-04) R50-AOT-L — 79.6 (2021-06-04) AOT-L — 78.3 (2021-06-04) AOT-B — 75.5 (2021-06-04) AOT-S — 73.9 (2021-06-04) AOT-T — 72.0 (2021-06-04) SwinB-AOT-L — 81.2 (2021-06-04) R50-AOT-L — 79.6 (2021-06-04) AOT-L — 78.3 (2021-06-04) AOT-B — 75.5 (2021-06-04) AOT-S — 73.9 (2021-06-04) AOT-T — 72.0 (2021-06-04) STCN — 79.9 (2021-06-09) STCN — 79.9 (2021-06-09) STCN — 79.9 (2021-06-09) HMMN — 78.6 (2021-09-23) HMMN — 78.6 (2021-09-23) HMMN — 78.6 (2021-09-23) RPCMVOS-Full-Res — 81.0 (2021-12-06) RPCMVOS — 79.2 (2021-12-06) RPCMVOS-Full-Res — 81.0 (2021-12-06) RPCMVOS — 79.2 (2021-12-06) RPCMVOS-Full-Res — 81.0 (2021-12-06) RPCMVOS — 79.2 (2021-12-06) SwinB-AOST (L'=3, MS) — 84.7 (2022-03-22) SwinB-AOTv2-L — 84.5 (2022-03-22) SwinB-AOST (L'=3) — 82.7 (2022-03-22) R50-AOST (L'=3) — 79.9 (2022-03-22) R50-AOST (L'=2) — 78.1 (2022-03-22) SwinB-AOST (L'=3, MS) — 84.7 (2022-03-22) SwinB-AOTv2-L — 84.5 (2022-03-22) SwinB-AOST (L'=3) — 82.7 (2022-03-22) R50-AOST (L'=3) — 79.9 (2022-03-22) R50-AOST (L'=2) — 78.1 (2022-03-22) SwinB-AOST (L'=3, MS) — 84.7 (2022-03-22) SwinB-AOTv2-L — 84.5 (2022-03-22) SwinB-AOST (L'=3) — 82.7 (2022-03-22) R50-AOST (L'=3) — 79.9 (2022-03-22) R50-AOST (L'=2) — 78.1 (2022-03-22) XMem (BL30K, MS) — 83.7 (2022-07-14) XMem (MS) — 83.1 (2022-07-14) XMem (BL30K, 600p) — 82.5 (2022-07-14) XMem (BL30K) — 81.2 (2022-07-14) XMem — 81.0 (2022-07-14) XMem (DAVIS and YouTubeVOS only) — 79.8 (2022-07-14) XMem (BL30K, MS) — 83.7 (2022-07-14) XMem (MS) — 83.1 (2022-07-14) XMem (BL30K, 600p) — 82.5 (2022-07-14) XMem (BL30K) — 81.2 (2022-07-14) XMem — 81.0 (2022-07-14) XMem (DAVIS and YouTubeVOS only) — 79.8 (2022-07-14) XMem (BL30K, MS) — 83.7 (2022-07-14) XMem (MS) — 83.1 (2022-07-14) XMem (BL30K, 600p) — 82.5 (2022-07-14) XMem (BL30K) — 81.2 (2022-07-14) XMem — 81.0 (2022-07-14) XMem (DAVIS and YouTubeVOS only) — 79.8 (2022-07-14) QDMN — 81.9 (2022-07-16) QDMN — 81.9 (2022-07-16) QDMN — 81.9 (2022-07-16) SwinB-DeAOT-L — 82.8 (2022-10-18) R50-DeAOT-L — 80.7 (2022-10-18) DeAOT-L — 77.9 (2022-10-18) DeAOT-B — 76.2 (2022-10-18) DeAOT-S — 75.4 (2022-10-18) DeAOT-T — 73.7 (2022-10-18) SwinB-DeAOT-L — 82.8 (2022-10-18) R50-DeAOT-L — 80.7 (2022-10-18) DeAOT-L — 77.9 (2022-10-18) DeAOT-B — 76.2 (2022-10-18) DeAOT-S — 75.4 (2022-10-18) DeAOT-T — 73.7 (2022-10-18) SwinB-DeAOT-L — 82.8 (2022-10-18) R50-DeAOT-L — 80.7 (2022-10-18) DeAOT-L — 77.9 (2022-10-18) DeAOT-B — 76.2 (2022-10-18) DeAOT-S — 75.4 (2022-10-18) DeAOT-T — 73.7 (2022-10-18) DEVA — 83.2 (2023-09-07) DEVA — 83.2 (2023-09-07) DEVA — 83.2 (2023-09-07) Cutie+ (base, MEGA) — 88.1 (2023-10-19) Cutie (base, MEGA) — 86.1 (2023-10-19) Cutie+ (base) — 85.9 (2023-10-19) Cutie+ (base, MEGA) — 88.1 (2023-10-19) Cutie (base, MEGA) — 86.1 (2023-10-19) Cutie+ (base) — 85.9 (2023-10-19) Cutie+ (base, MEGA) — 88.1 (2023-10-19) Cutie (base, MEGA) — 86.1 (2023-10-19) Cutie+ (base) — 85.9 (2023-10-19) JIMD-R50 — 83.9 (2024-09-22) JIMD-R50 — 83.9 (2024-09-22) JIMD-R50 — 83.9 (2024-09-22) OSVOS — 50.9 (2016-11-16) Lucid — 66.6 (2017-03-28) CINM — 67.5 (2018-03-26) PReMVOS — 71.6 (2018-07-24) STM — 72.2 (2019-04-01) CFBI — 74.8 (2020-03-18) KMN — 77.2 (2020-07-16) CFBI+ — 78.0 (2020-10-13) SwinB-AOT-L — 81.2 (2021-06-04) SwinB-AOST (L'=3, MS) — 84.7 (2022-03-22) Cutie+ (base, MEGA) — 88.1 (2023-10-19)
RankModel J&FJaccard (Mean)Jaccard (Recall)Jaccard (Decay)F-measure (Mean)F-measure (Recall)F-measure (Decay)FPS Extra Training Data PaperCodeYear
1 Cutie+ (base, MEGA) 88.184.7––91.4––17.9 ✓ Putting the Object Back into Video Object Segmentation hkchengrex/Cutie 2023
2 Cutie (base, MEGA) 86.182.4––89.9––36.4 ✓ Putting the Object Back into Video Object Segmentation hkchengrex/Cutie 2023
3 Cutie+ (base) 85.982.6––89.2––17.9 Putting the Object Back into Video Object Segmentation hkchengrex/Cutie 2023
4 SwinB-AOST (L'=3, MS) 84.780.9––88.5––1.3 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
5 SwinB-AOTv2-L 84.581.0––87.9––1.3 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
6 JIMD-R50 83.980.3––87.4––– Memory Matching is not Enough: Jointly Improving Memory Matching and Decoding for Video Object Segmentation 2024
7 XMem (BL30K, MS) 83.780.5––87.0––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
8 DEVA 83.279.6––86.8––25.3 ✓ Tracking Anything with Decoupled Video Segmentation hkchengrex/Tracking-Anything-with-DEVA 2023
9 XMem (MS) 83.179.7––86.4––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
10 SwinB-DeAOT-L 82.878.9––86.7––15.4 Decoupling Features in Hierarchical Propagation for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2022
11 SwinB-AOST (L'=3) 82.778.8––86.6––12.0 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
12 XMem (BL30K, 600p) 82.579.1––85.8––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
13 QDMN 81.978.1––85.4––– ✓ Learning Quality-aware Dynamic Memory for Video Object Segmentation workforai/qdmn 2022
14 XMem (BL30K) 81.277.6––84.7––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
14 SwinB-AOT-L 81.277.3––85.1––12.1 Associating Objects with Transformers for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2021
16 RPCMVOS-Full-Res 8177.6––84.3––– Reliable Propagation-Correction Modulation for Video Object Segmentation jerryx1110/rpcmvos 2021
16 XMem 81.077.4––84.5––– ✓ XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model hkchengrex/XMem · tianyuan168326/videosemanticcompression-pytorch 2022
18 R50-DeAOT-L 80.776.9––84.5––27.0 Decoupling Features in Hierarchical Propagation for Video Object Segmentation yoxu515/aot-benchmark · z-x-yang/AOT 2022
19 STCN 79.976.385.510.583.589.710.3– ✓ Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation hkchengrex/STCN · limingxing00/rde-vos-cvpr2022 · alipga/AMM_VOS 2021
19 R50-AOST (L'=3) 79.976.2––83.6––17.5 Scalable Video Object Segmentation with Identification Mechanism yoxu515/aot-benchmark · z-x-yang/AOT 2022
1–20 / 177 다음 → 페이지당 10 20 50 100