This repo is an extension of repo of temporal action localization/detection and related area (e.g. temporal action proposal) resources. Compared with the original repo, this repo adds more resource and updates several papers with code. Will keep up to date. Welcome to contribute together!
- Temporal Action Localization
- Weakly Supervised Temporal Action Localization
- Few-shot Learning
- [DBG] Fast Learning of Temporal Action Proposal via Dense Boundary Generator - Chunming Lin et al.,
AAAI 2020. [code] - [G-TAD] G-TAD: Sub-Graph Localization for Temporal Action Detection - Mengmeng Xu et al.,
CVPR 2020. [code] - [PBRNet] Progressive Boundary Refinement Network for Temporal Action Detection - Qinying Liu et al.,
AAAI 2020. - [AGCN] Graph Attention based Proposal 3D ConvNets for Action Detection - Jun Li et al.,
AAAI 2020.
- [PGCN] Graph Convolutional Networks for Temporal Action Localization - Runhao Zeng et al.,
ICCV 2019. [code] - [RAM] Graph Convolutional Networks for Temporal Action Localization - Peihao Chen et al.,
TMM 2019. - [BMN] BMN: Boundary-Matching Network for Temporal Action Proposal Generation - Tianwei Lin et al.,
ICCV 2019. - [GTAN] Gaussian Temporal Awareness Networks for Action Localization - Fuchen Long et al.,
CVPR 2019. - [DBS] Video Imprint Segmentation for Temporal Action Detection in Untrimmed Videos - Zhanning Gao et al.,
AAAI 2019. - [C-TCN] Deep Concept-wise Temporal Convolutional Networks for Action Localization - Xin Li et al.,
arXiv 2019.
- [TAL-Net] Rethinking the Faster R-CNN Architecture for Temporal Action Localization - Yuwei Chao et al.,
CVPR 2018. - [BSN] BSN: Boundary Sensitive Network for Temporal Action Proposal Generation - Tianwei Lin et al.,
ECCV 2018. [code] - [Action-Search] Action Search: Spotting Actions in Videos and Its Application to Temporal Action Localization - Humam Alwassel et al.,
ECCV 2018. [code] - [TPC] Exploring Temporal Preservation Networks for Precise Temporal Action Localization - Ke Yang et al.,
AAAI 2018. - [Self-Ad] A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning - Jingjia Huang et al.,
AAAI 2018.
- [SSN] Temporal Action Detection with Structured Segment Networks - Yue Zhao et al.,
ICCV 2017. [code] - [R-C3D] R-C3D: Region Convolutional 3D Network for Temporal Activity Detection - Huijuan Xu et al.,
ICCV 2017. [code] - [TCN] Temporal Context Network for Activity Localization in Videos - Xiyang Dai et al.,
ICCV 2017. - [TURN] TURN TAP: Temporal Unit Regression Network for Temporal Action Proposals - Jiyang Gao et al.,
ICCV 2017. [code] - [SST] SST: Single-Stream Temporal Action Proposals - Shyamal Buch et al.,
ICCV 2017. - [CDC] CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos - Zheng Shou et al.,
CVPR 2017. [code] - [SCC] SCC: Semantic Context Cascade for Efficient Action Detection - Fabian Caba Heilbron et al.,
CVPR 2017. - [SMS] Temporal Action Localization by Structured Maximal Sums - Zehuan Yuan et al.,
CVPR 2017.
- [S-CNN] Temporal Action Localization in Untrimmed Videos via Multi-stage CNNs - Zheng Shou et al.,
CVPR 2016. [code] - [PSDF] Temporal Action Localization with Pyramid of Score Distribution Features - Jun Yuan et al.,
CVPR 2016. - [FG] End-to-end Learning of Action Detection from Frame Glimpses in Videos - Serena Yeung et al.,
CVPR 2016. - [SLM] Temporal Action Detection Using a Statistical Language Model - Alexander Richard et al.,
CVPR 2016. - [DAPs] DAPs: Deep Action Proposals for Action Understanding - Victor Escorcia et al.,
ECCV 2016.
| Method | Conference | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] |
|---|---|---|---|---|---|---|---|---|
| DAPs | ECCV-2016 | - | - | - | - | 13.9 | - | - |
| SLM | CVPR-2016 | 39.7 | 35.7 | 30.0 | 23.2 | 15.2 | - | - |
| FG | CVPR-2016 | 48.9 | 44.0 | 36.0 | 26.4 | 17.1 | - | - |
| SMS | CVPR-2017 | 51.0 | 45.2 | 36.5 | 27.8 | 17.8 | - | - |
| PSDF | CVPR-2016 | 51.4 | 42.6 | 33.6 | 26.1 | 18.8 | - | - |
| S-CNN | CVPR-2016 | 47.7 | 43.5 | 36.3 | 28.7 | 19.0 | 10.3 | 5.3 |
| SST | ICCV-2017 | - | - | - | - | 23.0 | - | - |
| CDC | CVPR-2017 | - | - | 40.1 | 29.4 | 23.3 | 13.1 | 7.9 |
| TURN | ICCV-2017 | 54.0 | 50.9 | 44.1 | 34.9 | 25.6 | - | - |
| TCN | ICCV-2017 | - | - | - | 33.3 | 25.6 | 15.9 | 9.0 |
| Self-Ad | AAAI-2018 | - | - | - | - | 27.7 | - | - |
| TPC | AAAI-2018 | - | - | 44.1 | 37.1 | 28.2 | 20.6 | 12.7 |
| R-C3D | ICCV-2017 | 54.5 | 51.5 | 44.8 | 35.6 | 28.9 | - | - |
| SSN | ICCV-2017 | 66.0 | 59.4 | 51.9 | 41.0 | 29.8 | - | - |
| Action-Search | ECCV-2018 | - | - | 51.8 | 42.4 | 30.8 | 20.2 | 11.1 |
| DBS | AAAI-2019 | 56.7 | 54.7 | 50.6 | 43.1 | 34.3 | 24.4 | 14.7 |
| BSN | ECCV-2018 | - | - | 53.5 | 45.0 | 36.9 | 28.4 | 20.0 |
| AGCN | AAAI-2020 | 59.3 | 59.6 | 57.1 | 51.6 | 38.6 | 28.9 | 17.0 |
| GTAN | CVPR-2019 | 69.1 | 63.7 | 57.8 | 47.2 | 38.8 | - | - |
| BMN | ICCV-2019 | - | - | 56.0 | 47.4 | 38.8 | 29.7 | 20.5 |
| DBG | AAAI-2020 | - | - | 57.8 | 49.4 | 39.8 | 30.2 | 21.7 |
| TAL-Net | CVPR-2018 | 59.8 | 57.1 | 53.2 | 48.5 | 42.8 | 33.8 | 20.8 |
| RAM | TMM-2019 | 65.4 | 63.1 | 58.8 | 52.7 | 43.7 | - | - |
| PGCN | ICCV-2019 | 69.5 | 67.8 | 63.6 | 57.8 | 49.1 | - | - |
| PBRNet | AAAI-2020 | - | - | 58.5 | 54.6 | 51.3 | 41.8 | 29.5 |
| G-TAD | CVPR-2020 | - | - | 66.4 | 60.4 | 51.6 | 37.6 | 22.9 |
| Method | Conference | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] |
|---|---|---|---|---|---|---|---|---|
| C-TCN | arXiv | 72.2 | 71.4 | 68.0 | 62.3 | 52.1 | - | - |
| Method | Conference | [email protected] | [email protected] | [email protected] | IoU@Avg |
|---|---|---|---|---|---|
| R-C3D | ICCV-2017 | 26.8 | - | - | - |
| AGCN | AAAI-2020 | 30.4 | - | - | - |
| SCC | CVPR-2017 | 39.9 | 18.7 | 4.7 | 19.3 |
| TAL-Net | CVPR-2018 | 38.23 | 18.30 | 1.30 | 20.22 |
| RAM | TMM-2019 | 36.99 | 23.10 | 3.34 | 23.03 |
| TCN | ICCV-2017 | 37.49 | 23.47 | 4.47 | 23.58 |
| CDC | CVPR-2017 | 45.3 | 26.0 | 0.2 | 23.8 |
| DBS | CVPR-2019 | 43.2 | 25.8 | 6.1 | 26.1 |
| PGCN | ICCV-2019 | 42.90 | 28.14 | 2.47 | 26.99 |
| SSN | ICCV-2017 | 43.26 | 28.70 | 5.63 | 28.28 |
| BSN | ECCV-2018 | 46.45 | 29.96 | 8.02 | 30.03 |
| BMN | ICCV-2019 | 50.07 | 34.78 | 8.29 | 33.85 |
| G-TAD | CVPR-2020 | 50.36 | 34.60 | 9.02 | 34.09 |
| GTAN | CVPR-2019 | 52.61 | 34.14 | 8.91 | 34.31 |
| PBRNet | AAAI-2020 | 53.96 | 34.97 | 8.98 | 35.01 |
| Method | Conference | [email protected] | [email protected] | [email protected] | IoU@Avg |
|---|---|---|---|---|---|
| C-TCN | arXiv | 47.6 | 31.9 | 6.2 | 31.1 |
- [DGAM] Weakly-Supervised Action Localization by Generative Attention Modeling - Baifeng Shi et al.,
CVPR2020[code] - [UncertaintyBM] Background Modeling via Uncertainty Estimation
for Weakly-supervised Action Localization - Pilhyeon Lee et al.,
Arxiv2020[code] - [RPN] Relational Prototypical Network for Weakly Supervised Temporal Action Localization - Linjiang Huang et al.,
AAAI 2020. - [BaSNet] Background Suppression Network for Weakly-supervised Temporal Action Localization - Pilhyeon Lee et al.,
AAAI 2020. - [DML] Weakly Supervised Temporal Action Localization Using Deep Metric Learning - Ashraful Islam et al.,
WACV 2020. [code] - [MCASL] Action Graphs: Weakly-supervised Action Localization with Graph Convolution Networks - Maheen Rashid et al.,
WACV 2020. [code] - [WSGN] Weakly Supervised Gaussian Networks for Action Detection - Basura Fernando et al.,
WACV 2020.
- [3C-Net] 3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization - Sanath Narayan et al.,
ICCV-2019[code] - [IWO-Net] Breaking Winner-Takes-All: Iterative-Winners-Out Networks for Weakly Supervised Temporal Action Localization - Runhao Zeng et al.,
TIP 2019. - [BM] Weakly-supervised Action Localization with Background Modeling - Phuc Xuan Nguyen et al.,
ICCV 2019. - [TSM] Temporal Structure Mining for Weakly Supervised Action Detection - Tan Yu et al.,
ICCV 2019. - [CleanNet] Weakly Supervised Temporal Action Localization through Contrast based Evaluation Networks - Ziyi Liu et al.,
ICCV 2019. - [CMCS] Completeness Modeling and Context Separation for Weakly Supervised Temporal Action Localization - Daochang Liu et al.,
CVPR 2019. [code] - [STAR] Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection - Yunlu Xu et al.,
AAAI 2019.
- [W-TALC] W-TALC: Weakly-supervised Temporal Activity Localization and Classification - Sujoy Paul et al.,
ECCV 2018. [code] - [AutoLoc] AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos - Zheng Shou et al.,
ECCV 2018. [code] - [STPN] Weakly Supervised Action Localization by Sparse Temporal Pooling Network [code1] [code2] - Phuc Nguyen et al.,
CVPR 2018. - [One-Shot] One-Shot Action Localization by Learning Sequence Matching Network - Hongtao Yang et al.,
CVPR 2018.
- [UNet] UntrimmedNets for Weakly Supervised Action Recognition and Detection - Limin Wang et al.,
CVPR 2017. [code] - [H&S] Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization - Krishna Kumar Singh et al.,
CVPR 2017.
| Method | Conference | Feature | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] |
|---|---|---|---|---|---|---|---|---|---|
| H&S | ICCV-2017 | - | 36.44 | 27.84 | 19.49 | 12.66 | 6.84 | - | - |
| UNet | CVPR-2017 | - | 44.4 | 37.7 | 28.2 | 21.1 | 13.7 | - | - |
| One-Shot | CVPR-2018 | - | - | - | - | - | 14.7 | - | - |
| STPN | CVPR-2018 | UNT | 52.0 | 44.7 | 35.5 | 25.8 | 16.9 | 9.9 | 4.3 |
| STPN | CVPR-2018 | UNT | 52.1 | 44.2 | 34.7 | 26.1 | 17.7 | 10.1 | 4.9 |
| IWO-Net | TIP-2019 | - | 57.6 | 48.9 | 38.9 | 29.3 | 20.5 | - | - |
| WSGN | WACV-2020 | - | 55.3 | 47.6 | 38.9 | 30.0 | 21.1 | - | - |
| AutoLoc | ECCV-2018 | UNT | - | - | 35.8 | 29.0 | 21.2 | 13.4 | 5.8 |
| W-TAL | ECCV-2018 | I3D | 55.2 | 49.6 | 40.1 | 31.1 | 22.8 | - | 7.6 |
| STAR | AAAI-2019 | - | 68.8 | 60.0 | 48.7 | 34.7 | 23.0 | - | - |
| CMCS | CVPR-2019 | I3D | 57.4 | 50.8 | 41.2 | 32.1 | 23.1 | 15.0 | 7.0 |
| CleanNet | ICCV-2019 | UNT | 68.8 | 60.0 | 37.0 | 30.9 | 23.9 | 13.9 | 7.1 |
| TSM | ICCV-2019 | I3D | - | - | 39.5 | - | 24.5 | - | 7.1 |
| MCASL | WACV-2020 | - | 63.7 | 56.9 | 47.3 | 36.4 | 26.1 | - | - |
| BM | ICCV-2019 | I3D | 60.4 | 56.0 | 46.6 | 37.5 | 26.8 | 17.6 | 9.0 |
| BaSNet | AAAI-2020 | UNT | 58.2 | 52.3 | 44.6 | 36.0 | 27.0 | 18.6 | 10.4 |
| RPN | AAAI-2020 | I3D | 62.3 | 57.0 | 48.2 | 37.2 | 27.9 | 16.7 | 8.1 |
| DML | AAAI-2020 | - | 62.3 | - | 46.8 | - | 29.6 | - | 9.7 |
| [3C-Net] | ICCV-2019 | I3D | 59.1 | 53.5 | 44.2 | 34.1 | 26.6 | 8.1 | |
| UncertaintyBM | Arxiv-2020 | I3D | - | 46.9 | 39.2 | 30.7 | 20.8 | 12.5 | |
| DGAM | CVPR-2020 | I3D | 60.0 | 54.2 | 46.8 | 38.2 | 28.8 | 19.8 | 11.4 |
| Method | Conference | [email protected] | [email protected] | [email protected] | IoU@Avg |
|---|---|---|---|---|---|
| STPN | CVPR-2018 | 29.3 | 16.9 | 2.6 | 20.07 |
| IWO-Net | TIP-2019 | 29.8 | 17.6 | 4.7 | - |
| TSM | ICCV-2019 | 30.3 | 19.0 | 4.5 | - |
| STAR | AAAI-2019 | 31.1 | 18.8 | 4.7 | - |
| CMCS | CVPR-2019 | 34.0 | 20.9 | 5.7 | 21.2 |
| BaSNet | AAAI-2019 | 34.5 | 22.5 | 4.9 | 22.2 |
| BM | ICCV-2019 | 36.4 | 19.2 | 2.9 | - |
| Method | Conference | [email protected] | [email protected] | [email protected] | IoU@Avg |
|---|---|---|---|---|---|
| UNet | CVPR-2017 | 7.4 | 3.2 | 0.7 | - |
| AutoLoc | ECCV-2018 | 27.3 | 15.1 | 3.3 | - |
| TSM | ICCV-2019 | 28.3 | 17.0 | 3.5 | - |
| MCASL | AAAI-2020 | 29.4 | - | - | - |
| STAR | AAAI-2019 | 31.1 | 18.8 | 4.7 | - |
| DML | AAAI-2020 | 35.2 | - | - | - |
| W-TALC | ECCV-2018 | 37.0 | - | - | 18.0 |
| CleanNet | ICCV-2019 | 37.1 | 20.3 | 5.0 | 21.6 |
| CMCS | CVPR-2019 | 36.8 | 22.0 | 5.6 | 22.4 |
| RPN | AAAI-2020 | 37.6 | 23.9 | 5.4 | 23.3 |
| BaSNet | AAAI-2020 | 38.5 | 24.2 | 5.6 | 24.3 |
| 3C-Net | ICCV-2019 | 37.2 | 23.7 | 9.2 | 21.7 |
| UncertaintyBM | Arxiv-2020 | 40.3 | 25.1 | 5.9 | 25.4 |
| DGAM | CVPR-2020 | 41.0 | 23.5 | 5.3 | 24.4 |
- [One-Shot] One-Shot Action Localization by Learning Sequence Matching Network - Hongtao Yang et al.,
CVPR 2018. - [Sim R-C3D] Similarity R-C3D for Few-shot Temporal Activity Detection - Huijuan Xu et al.,
Arxiv 2018.
| Method | Conference | Feature | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] | [email protected] |
|---|---|---|---|---|---|---|---|---|---|
| One-Shot | CVPR-2018 | - | - | - | - | - | 14.7 | - | - |
| Sim R-C3D | Arxiv-2018 | - | - | - | - | - | 28.1 | - | - |
| Method | Conference | [email protected] | [email protected] | [email protected] | IoU@Avg |
|---|---|---|---|---|---|
| Sim R-C3D | Arxiv-2018 | 51.6 | - | - | 34.6 |
| Method | Conference | [email protected] | [email protected] | [email protected] | IoU@Avg |
|---|---|---|---|---|---|
| One-shot | CVPR-2018 | 23.1 | - | - | 10.0 |
| Sim R-C3D | Arxiv-2018 | 45.8 | - | - | 28.2 |