Action Segmentation
Action Segmentation is a challenging problem in high-level video understanding. In its simplest form, Action Segmentation aims to segment a temporally untrimmed video by time and label each segmented part with one of pre-defined action labels. The results of Action Segmentation can be further used as input to various applications, such as video-to-text and action localization.
Source: TricorNet: A Hybrid Temporal Convolutional and Recurrent Network for Video Action Segmentation
Papers
Showing 1–10 of 219 papers
All datasetsBreakfast50 SaladsGTEACOINAssembly101JIGSAWSYoutube INRIA Instructional50SaladsMPII Cooking 2 Dataset
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | AdaFocus (newly extracted I3D-features, LT-Context model) | Average F1 | 76.2 | — | Unverified |
| 2 | FACT (efficient hybrid of convolution and transformer model) | Average F1 | 74.7 | — | Unverified |
| 3 | ASQuery | Average F1 | 74.6 | — | Unverified |
| 4 | BIT | Average F1 | 73.7 | — | Unverified |
| 5 | DiffAct | Average F1 | 73.6 | — | Unverified |
| 6 | BaFormer | Average F1 | 72.4 | — | Unverified |
| 7 | CETNet | Average F1 | 71.8 | — | Unverified |
| 8 | SF-TMN(ASFormer) | Average F1 | 71.6 | — | Unverified |
| 9 | RF++-SSTDA | Acc | 70.8 | — | Unverified |
| 10 | ASPnet | Average F1 | 70.6 | — | Unverified |