paper-with-me

Unsupervised Video Object Segmentation 벤치마크

Unsupervised Video Object Segmentation on YouTube-Objects

32개 결과 · ⬇ CSV · JSON

J

65.5 67.9 70.3 72.7 75.1 2018-09 2026-09 PDB — 65.5 (2018-09-01) PDB — 65.5 (2018-09-01) AGS — 69.7 (2019-06-01) AGS — 69.7 (2019-06-01) AGNN — 70.8 (2020-01-19) COSNet — 70.5 (2020-01-19) AGNN — 70.8 (2020-01-19) COSNet — 70.5 (2020-01-19) MATNet — 69.0 (2020-03-09) MATNet — 69.0 (2020-03-09) AMC-Net — 71.1 (2021-01-01) AMC-Net — 71.1 (2021-01-01) RTNet — 70.1 (2021-06-19) RTNet — 70.1 (2021-06-19) TMO (RN-101) — 71.5 (2022-09-04) TMO (MiT-b1) — 71.1 (2022-09-04) TMO (RN-101) — 71.5 (2022-09-04) TMO (MiT-b1) — 71.1 (2022-09-04) DPA — 73.7 (2022-11-22) DPA — 73.7 (2022-11-22) AMP — 75.0 (2023-03-18) AMP — 75.0 (2023-03-18) TMO++ (MiT-b1, MS) — 73.5 (2023-09-26) TMO++ (RN-101) — 73.1 (2023-09-26) TMO++ (MiT-b1) — 73.0 (2023-09-26) TMO++ (MiT-b1, MS) — 73.5 (2023-09-26) TMO++ (RN-101) — 73.1 (2023-09-26) TMO++ (MiT-b1) — 73.0 (2023-09-26) FakeFlow — 75.1 (2024-07-16) FakeFlow — 75.1 (2024-07-16) PDB — 65.5 (2018-09-01) AGS — 69.7 (2019-06-01) AGNN — 70.8 (2020-01-19) AMC-Net — 71.1 (2021-01-01) TMO (RN-101) — 71.5 (2022-09-04) DPA — 73.7 (2022-11-22) AMP — 75.0 (2023-03-18) FakeFlow — 75.1 (2024-07-16)
RankModel J PaperCodeYear
1 FakeFlow 75.1 Improving Unsupervised Video Object Segmentation via Fake Flow Generation 2024
2 AMP 75.0 Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation xiaoqi-zhao-dlut/multi-source-aps-zvos 2023
3 DPA 73.7 Dual Prototype Attention for Unsupervised Video Object Segmentation hydragon516/dpa 2022
4 TMO++ (MiT-b1, MS) 73.5 Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation suhwan-cho/tmo 2023
5 TMO++ (RN-101) 73.1 Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation suhwan-cho/tmo 2023
6 TMO++ (MiT-b1) 73.0 Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation suhwan-cho/tmo 2023
7 TMO (RN-101) 71.5 Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation suhwan-cho/tmo · ahasan-haque/TMO-RAFT 2022
8 AMC-Net 71.1 Learning Motion-Appearance Co-Attention for Zero-Shot Video Object Segmentation isyangshu/amc-net 2021
8 TMO (MiT-b1) 71.1 Treating Motion as Option to Reduce Motion Dependency in Unsupervised Video Object Segmentation suhwan-cho/tmo · ahasan-haque/TMO-RAFT 2022
10 AGNN 70.8 Zero-Shot Video Object Segmentation via Attentive Graph Neural Networks carrierlxk/AGNN 2020
11 COSNet 70.5 See More, Know More: Unsupervised Video Object Segmentation with Co-Attention Siamese Networks carrierlxk/COSNet 2020
11 WCS-Net 70.5 Unsupervised Video Object Segmentation with Joint Hotspot Tracking
13 RTNet 70.1 Reciprocal Transformations for Unsupervised Video Object Segmentation OliverRensu/RTNet 2021
14 AGS 69.7 Learning Unsupervised Video Object Segmentation Through Visual Attention wenguanwang/AGS 2019
15 MATNet 69.0 Motion-Attentive Transition for Zero-Shot Video Object Segmentation tfzhou/MATNet 2020
16 PDB 65.5 Pyramid Dilated Deeper ConvLSTM for Video Salient Object Detection 2018
17 FakeFlow 75.1 Improving Unsupervised Video Object Segmentation via Fake Flow Generation 2024
18 AMP 75.0 Adaptive Multi-source Predictor for Zero-shot Video Object Segmentation xiaoqi-zhao-dlut/multi-source-aps-zvos 2023
19 DPA 73.7 Dual Prototype Attention for Unsupervised Video Object Segmentation hydragon516/dpa 2022
20 TMO++ (MiT-b1, MS) 73.5 Treating Motion as Option with Output Selection for Unsupervised Video Object Segmentation suhwan-cho/tmo 2023
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