| Semantic2Graph |
- F1@10%
- 95.7
- F1@50%
- 91.3
- Acc
- 89.8
- Edit
- 92.0
- F1@25%
- 94.2
|
Semantic2Graph: Graph-based Multi-modal Feature Fusion for Action Segmentation in Videos 2022-09-13 |
연결 없음 |
| FACT |
- F1@10%
- 96.1
- F1@50%
- 87.5
- Acc
- 84.5
- Edit
- 93.5
- F1@25%
- 95.6
|
FACT: Frame-Action Cross-Attention Temporal Modeling for Efficient Action Segmentation 2024-01-01 |
코드 1 |
| DiffAct |
- F1@10%
- 92.5
- F1@50%
- 84.7
- Acc
- 82.2
- Edit
- 89.6
- F1@25%
- 91.5
|
Diffusion Action Segmentation 2023-03-31 |
코드 1 |
| BaFormer |
- F1@10%
- 92.0
- F1@50%
- 83.5
- Acc
- 83.0
- Edit
- 88.7
- F1@25%
- 91.3
|
Efficient Temporal Action Segmentation via Boundary-aware Query Voting 2024-05-25 |
코드 1 |
| SF-TMN(ASFormer) |
- F1@10%
- 91.9
- F1@50%
- 83.1
- Acc
- 83.0
- Edit
- 88.9
- F1@25%
- 90.7
|
SF-TMN: SlowFast Temporal Modeling Network for Surgical Phase Recognition 2023-06-15 |
연결 없음 |
| Br-Prompt+ASFormer |
- F1@10%
- 94.1
- F1@50%
- 83.0
- Acc
- 81.2
- Edit
- 91.6
- F1@25%
- 92.0
|
Bridge-Prompt: Towards Ordinal Action Understanding in Instructional Videos 2022-03-26 |
코드 1 |
| DPRN |
- F1@10%
- 92.9
- F1@50%
- 82.9
- Acc
- 82.0
- Edit
- 90.9
- F1@25%
- 92.0
|
Maximization and restoration: Action segmentation through dilation passing and temporal reconstruction 2022-05-02 |
연결 없음 |
| BIT |
- F1@10%
- 94.8
- F1@50%
- 82.6
- Acc
- 82.0
- Edit
- 92.6
- F1@25%
- 92.8
|
BIT: Bi-Level Temporal Modeling for Efficient Supervised Action Segmentation 2023-08-28 |
연결 없음 |
| CETNet |
- F1@10%
- 91.8
- F1@50%
- 81.3
- Acc
- 80.3
- Edit
- 87.9
- F1@25%
- 91.2
|
Cross-Enhancement Transformer for Action Segmentation 2022-05-19 |
코드 1 |
| UVAST |
- F1@10%
- 92.7
- F1@50%
- 81
- Acc
- 80.2
- Edit
- 92.1
- F1@25%
- 91.3
|
Unified Fully and Timestamp Supervised Temporal Action Segmentation via Sequence to Sequence Translation 2022-09-01 |
코드 1 · 코드 2 |
| ASRF |
- F1@10%
- 89.4
- F1@50%
- 79.8
- Acc
- 77.3
- Edit
- 83.7
- F1@25%
- 87.8
|
Alleviating Over-segmentation Errors by Detecting Action Boundaries 2020-07-14 |
코드 1 |
| ASFormer |
- F1@10%
- 90.1
- F1@50%
- 79.2
- Acc
- 79.7
- Edit
- 84.6
- F1@25%
- 88.8
|
ASFormer: Transformer for Action Segmentation 2021-10-16 |
코드 1 |
| SSTDA |
- F1@10%
- 90.0
- F1@50%
- 78.0
- Acc
- 79.8
- Edit
- 86.2
- F1@25%
- 89.1
|
Action Segmentation with Joint Self-Supervised Temporal Domain Adaptation 2020-03-05 |
코드 1 |
| ETSN |
- F1@10%
- 91.1
- F1@50%
- 77.9
- Acc
- 78.2
- Edit
- 86.2
- F1@25%
- 90.0
|
Efficient Two-Step Networks for Temporal Action Segmentation 2021-04-30 |
코드 1 |
| C2F-TCN |
- F1@10%
- 90.3
- F1@50%
- 77.7
- Acc
- 80.8
- Edit
- 86.4
- F1@25%
- 88.8
|
Coarse to Fine Multi-Resolution Temporal Convolutional Network 2021-05-23 |
코드 1 |
| BCN |
- F1@10%
- 88.5
- F1@50%
- 77.3
- Acc
- 79.8
- Edit
- 84.4
- F1@25%
- 87.1
|
Boundary-Aware Cascade Networks for Temporal Action Segmentation 논문 날짜 미기재 |
코드 1 |
| SSTDA + HASR |
- F1@10%
- 90.9
- F1@50%
- 76.4
- Acc
- 78.7
- Edit
- 87.5
- F1@25%
- 88.6
|
Refining Action Segmentation With Hierarchical Video Representations 2021-01-01 |
코드 1 |
| DA |
- F1@10%
- 90.5
- F1@50%
- 76.2
- Acc
- 80.0
- Edit
- 85.8
- F1@25%
- 88.4
|
Action Segmentation with Mixed Temporal Domain Adaptation 2021-04-15 |
연결 없음 |
| MS-TCN++ |
- F1@10%
- 88.8
- F1@50%
- 76.0
- Acc
- 80.1
- Edit
- 83.5
- F1@25%
- 85.7
|
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation 2020-06-16 |
코드 1 |
| MS-TCN++(sh) |
- F1@10%
- 88.2
- F1@50%
- 75.9
- Acc
- 79.7
- Edit
- 83.0
- F1@25%
- 86.2
|
MS-TCN++: Multi-Stage Temporal Convolutional Network for Action Segmentation 2020-06-16 |
코드 1 |
| ASRF + HASR |
- F1@10%
- 89.2
- F1@50%
- 74.8
- Acc
- 76.9
- Edit
- 84.5
- F1@25%
- 87.2
|
Refining Action Segmentation With Hierarchical Video Representations 2021-01-01 |
코드 1 |
| MS-TCN |
- F1@10%
- 87.5
- F1@50%
- 74.6
- Acc
- 79.2
- Edit
- 81.4
- F1@25%
- 85.4
|
MS-TCN: Multi-Stage Temporal Convolutional Network for Action Segmentation 2019-03-05 |
코드 1 · 코드 2 |
| EUT |
- F1@10%
- 88.2
- F1@50%
- 74
- Acc
- 77
- Edit
- 83.9
- F1@25%
- 87.2
|
Do we really need temporal convolutions in action segmentation? 2022-05-26 |
코드 1 |
| DS-TCN |
- F1@10%
- 88.30
- F1@50%
- 72.84
- Acc
- 78.10
- Edit
- 84.05
- F1@25%
- 85.44
|
Depthwise Separable Temporal Convolutional Network for Action Segmentation 2021-01-19 |
연결 없음 |
| AUL |
- F1@10%
- 88.2
- F1@50%
- 67.3
- Acc
- 69.2
- Edit
- 84.0
- F1@25%
- 85.5
|
Is Weakly-supervised Action Segmentation Ready For Human-Robot Interaction? No, Let's Improve It With Action-union Learning 2023-10-22 |
코드 1 |
| TDRN |
- F1@10%
- 79.2
- F1@50%
- 62.7
- Acc
- 70.1
- Edit
- 74.1
- F1@25%
- 74.4
|
Temporal Deformable Residual Networks for Action Segmentation in Videos 2018-06-01 |
연결 없음 |
| ED-TCN |
- F1@10%
- 72.2
- F1@50%
- 56.0
- Acc
- 64.0
- Edit
- -
- F1@25%
- 69.3
|
Temporal Convolutional Networks for Action Segmentation and Detection 2016-11-16 |
코드 1 · 코드 2 · 코드 3 · 코드 4 · 코드 5 |
| ST-CNN |
- F1@10%
- 58.7
- F1@50%
- 41.9
- Acc
- 60.6
- Edit
- -
- F1@25%
- 54.4
|
Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation 2016-02-09 |
연결 없음 |