Deep_Learning_Temporal_Action_Detection

KO | EN

gitlite — search

#javascript #react #ai #typescript #golang #go #machine-learning #rust #deep-learning #nodejs #windows #awesome #security #mcp

Deep_Learning_Temporal_Action_Detection

(★ 56)

A list of papers of temporal action detectino using deep learning.

Deep_Learning_Temporal_Action_Detection Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Deep Learning Temporal Action Detection

*Last updated: 2019/9/25*

## Performance Table

|   Detector    | THUMOS (mAP@IoU=0.5) | ANET (mAP@IoU=0.5)  | Speed | Published In |
|:-------------:|:--------------------:|:-------------------:|-------|-------------:|
|      LAF      |         4.4          |          -          |       |    ACMMM'15   |
|    RNN & RL   |         17.1         |          -          |       |    CVPR'16   |
|      PSDF     |         18.8         |          -          |       |    CVPR'16   |
|      SSAD     |         24.6         |          -          |       |    CVPR'16   |
|      SCNN     |         19.0         |          -          |       |    CVPR'16   |
|     SCNNv2    |         19.0         |          -          |       |    WACV'16   |
|      CBR      |         31.0         |          -          |       |    BMVC'17   |
|      SMS      |         14.8         |          -          |       |    CVPR'17   |
| UntrimmedNets |         13.7         |         7.2         |       |    CVPR'17   |
|      TCN      |         25.6         |         23.6        |       |    ICCV'17   |
|    ETE SSTAD  |         29.2         |          -          |       |    BMVC'17   |
|      CDC      |         23.3         |         22.9        |  500  |    ICCV'17   |
|      SMS      |         17.8         |          -          |       |    CVPR'17   |
|      SCC      |         19.3         |          -          |       |    CVPR'17   |
|      TAG      |         28.3         |          -          |       |    CVPR'17   |
|      SST      |         19.3         |          -          |       |    CVPR'17   |
|     SSTAD     |         24.6         |          -          |       |    ACMMM'17  |
|    TURN-TAP   |         25.6         |          -          |  880  |    ICCV'17   |
|     R-C3D     |         28.9         |         16.7        |       |    ICCV'17   |
|    TAG+SSN    |         29.1         |         28.3        |       |    ICCV'17   |
|      ETP      |         34.2         |          -          |       |    CVPR'18   |
|     TAL-Net   |         42.0         |         38.2        |       |    CVPR'18   |
|     STPN      |         16.9         |         29.3        |       |    CVPR'18   |
|      TPN      |         27.6         |          -          |       |    AAAI'18   |
|      SAP      |         27.7         |          -          |       |    AAAI'18   |
|     WSTAD     |         15.9         |         27.3        |       |    ACMMM'18  |
|      BSN      |         36.9         |          -          |       |    ECCV'18   |
|    AutoLoc    |         21.2         |         27.3        |       |    ECCV'18   |
|    W-TALC     |         22.8         |         37.0        |       |    ECCV'18   |
|     CPMN      |         16.1         |         39.3        |       |    ACMMM'18  |
|     STAR      |         23.0         |         31.1        |       |    AAAI'19   |
|     BMN       |         38.8         |         39.4        |       |    ICCV'19   |
|     MGG       |         39.9         |           -         |       |    ICCV'19   |

## Dataset
- **[THUMOS]** THUMOS Challenge 2014 |[`[Homepage]`](http://crcv.ucf.edu/THUMOS14/)

- **[Activity-Net]**  A Large-Scale Video Benchmark for Human Activity Understanding |[`[Homepage]`](http://activity-net.org/index.html)

- **[COIN]**  A Large-scale Dataset for Comprehensive Instructional Video Analysis |[`[Homepage]`](https://coin-dataset.github.io/)

## 2015
- **[LAF]** Temporal Localization of Fine-Grained Actions in Videos by Domain Transfer from Web Images  | **[ACMMM'15]** |[`[pdf]`](http://cn.arxiv.org/pdf/1504.00983.pdf)

## 2016
- **[RNN & RL]** End-to-end learning of action detection from frame glimpses in videos  | **[CVPR'16]** |[`[pdf]`](https://arxiv.org/pdf/1511.06984.pdf)

- **[PSDF]** Temporal Action Localization with Pyramid of Score Distribution Features   | **[CVPR'16]** |[`[pdf]`](http://openaccess.thecvf.com/content_cvpr_2016/papers/Yuan_Temporal_Action_Localization_CVPR_2016_paper.pdf)

- **[SCNN]** Temporal action localization in untrimmed videos via multi-stage CNNs  | **[CVPR'16]** |[`[pdf]`](https://arxiv.org/pdf/1601.02129.pdf)

- **[SCNNv2]** Efficient Action Detection in Untrimmed Videos via Multi-Task Learning  | **[WACV'16]** |[`[pdf]`](https://arxiv.org/pdf/1612.07403.pdf)

## 2017
- **[SSAD]** Single Shot Temporal Action Detection  | **[ACMMM'17]** |[`[pdf]`](https://arxiv.org/pdf/1710.06236.pdf)

- **[CBR]** Cascaded Boundary Regression for Temporal Action Detection  | **[BMVC'17]** |[`[pdf]`](https://arxiv.org/pdf/1705.01180.pdf)

- **[SMS]**  Temporal Action Localization by Structured Maximal Sums  | **[CVPR'17]** |[`[pdf]`](http://cn.arxiv.org/pdf/1704.04671v1.pdf)
- 
- **[UntrimmedNets]**  UntrimmedNets for Weakly Supervised Action Recognition and Detection  | **[CVPR'17]** |[`[pdf]`](http://cn.arxiv.org/pdf/1703.03329.pdf)

- **[TCN]** Temporal Context Network for Activity Localization in Videos  | **[ICCV'17]** |[`[pdf]`](https://arxiv.org/pdf/1708.02349.pdf)

- **[SCC]** Semantic Context Cascade for Efficient Action Detection  | **[CVPR'17]** |[`[pdf]`](http://openaccess.thecvf.com/content_cvpr_2017/papers/Heilbron_SCC_Semantic_Context_CVPR_2017_paper.pdf)

- **[SSTAD]** Single Shot Temporal Action Detection  | **[ACMMM'17]** |[`[pdf]`](https://arxiv.org/pdf/1710.06236.pdf)

- **[ETE SSTAD]** End-to-End, Single-Stream Temporal Action Detection in Untrimmed Videos  | **[BMVC'17]** |[`[pdf]`](http://vision.stanford.edu/pdf/buch2017bmvc.pdf)

- **[SST]** Single-stream temporal action proposals  | **[CVPR'17]** |[`[pdf]`](http://vision.stanford.edu/pdf/buch2017cvpr.pdf)

- **[TURN-TAP]** Temporal Unit Regression Network for Temporal Action Proposals  | **[ICCV'17]** |[`[pdf]`](https://arxiv.org/pdf/1703.06189.pdf)

- **[Hide-and-Seek]** Hide-and-Seek: Forcing a Network to be Meticulous for Weakly-supervised Object and Action Localization  | **[ICCV'17]** |[`[pdf]`](http://cn.arxiv.org/pdf/1704.04232.pdf)

- **[TAG]** A Pursuit of Temporal Accuracy in General Activity Detection  | **[CVPR'17]** |[`[pdf]`](https://arxiv.org/pdf/1703.02716.pdf)

## 2018
- **[ETP]** Precise Temporal Action Localization by Evolving Temporal Proposals  | **[CVPR'18]** |[`[pdf]`](https://arxiv.org/pdf/1804.04803.pdf)

- **[TAL-Net]** Rethinking the Faster R-CNN Architecture for Temporal Action Localization  | **[CVPR'18]** |[`[pdf]`](https://arxiv.org/pdf/1804.07667.pdf)

- **[STPN]** Weakly Supervised Action Localization by Sparse Temporal Pooling Network| **[CVPR'18]** |[`[pdf]`](http://cn.arxiv.org/pdf/1712.05080.pdf)

- **[TPN]** Exploring Temporal Preservation Networks for Precise Temporal Action Localization  | **[AAAI'18]** |[`[pdf]`](https://arxiv.org/pdf/1708.03280.pdf)

- **[SAP]** A Self-Adaptive Proposal Model for Temporal Action Detection based on Reinforcement Learning  | **[AAAI'18]** |[`[pdf]`](https://arxiv.org/pdf/1706.07251.pdf)

- **[WSTAD]** Step-by-step Erasion, One-by-one Collection: A Weakly Supervised Temporal Action Detector | **[ACMMM'18]** |[`[pdf]`](http://cn.arxiv.org/pdf/1807.02929.pdf)

- **[BSN]** Boundary Sensitive Network for Temporal Action Proposal Generation  | **[ECCV'18]** |[`[pdf]`](https://arxiv.org/pdf/1806.02964.pdf)

- **[AutoLoc]** AutoLoc: Weakly-supervised Temporal Action Localization in Untrimmed Videos  | **[ECCV'18]** |[`[pdf]`](http://cn.arxiv.org/pdf/1807.08333.pdf)

- **[W-TALC]** W-TALC: Weakly-supervised Temporal Activity Localization and Classification  | **[ECCV'18]** |[`[pdf]`](http://cn.arxiv.org/pdf/1807.10418)

- **[CPMN]** Cascaded Pyramid Mining Network for Weakly Supervised Temporal Action Localization  | **[ACCV'18]** |[`[pdf]`](http://cn.arxiv.org/pdf/1810.11794.pdf)

## 2019
- **[STAR]** Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection   | **[AAAI'19]** |[`[pdf]`](http://cn.arxiv.org/pdf/1811.07460.pdf) 
- **[BMN]** BMN: Boundary-Matching Network for Temporal Action Proposal Generation   | **[ICCV'19]** |[`[pdf]`](https://arxiv.org/pdf/1907.09702.pdf) 
- **[MGG]** Multi-granularity Generator for Temporal Action Proposal   | **[CVPR'19]** |[`[pdf]`](https://arxiv.org/pdf/1811.11524.pdf)

Deep_Learning_Temporal_Action_Detection

Deep_Learning_Temporal_Action_Detection Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Deep_Learning_Temporal_Action_Detection

Deep_Learning_Temporal_Action_Detection Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README