# ACGNet: Action Complement Graph Network for Weakly-supervised Temporal Action Localization

arXiv: https://arxiv.org/abs/2112.10977 · HTML: https://mlsanity.com/paper/2112.10977/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 35 of its 50 references that are in the map.
- First posted on arXiv 21 Dec 2021.

## Builds on (most cited first, 30 of 35)

- [Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset](https://mlsanity.com/paper/1705.07750/) (2017)
- [SlowFast Networks for Video Recognition](https://mlsanity.com/paper/1812.03982/) (2018)
- [BMN: Boundary-Matching Network for Temporal Action Proposal Generation](https://mlsanity.com/paper/1907.09702/) (2019)
- [YouTube-8M: A Large-Scale Video Classification Benchmark](https://mlsanity.com/paper/1609.08675/) (2016)
- [BSN: Boundary Sensitive Network for Temporal Action Proposal Generation](https://mlsanity.com/paper/1806.02964/) (2018)
- [Temporal Action Detection with Structured Segment Networks](https://mlsanity.com/paper/1704.06228/) (2017)
- [G-TAD: Sub-Graph Localization for Temporal Action Detection](https://mlsanity.com/paper/1911.11462/) (2019)
- [Long-Term Feature Banks for Detailed Video Understanding](https://mlsanity.com/paper/1812.05038/) (2018)
- [The THUMOS Challenge on Action Recognition for Videos "in the Wild"](https://mlsanity.com/paper/1604.06182/) (2016)
- [Graph Convolutional Networks for Temporal Action Localization](https://mlsanity.com/paper/1909.03252/) (2019)
- [Rethinking the Faster R-CNN Architecture for Temporal Action Localization](https://mlsanity.com/paper/1804.07667/) (2018)
- [TEA: Temporal Excitation and Aggregation for Action Recognition](https://mlsanity.com/paper/2004.01398/) (2020)
- [Gaussian Temporal Awareness Networks for Action Localization](https://mlsanity.com/paper/1909.03877/) (2019)
- [UntrimmedNets for Weakly Supervised Action Recognition and Detection](https://mlsanity.com/paper/1703.03329/) (2017)
- [Single Shot Temporal Action Detection](https://mlsanity.com/paper/1710.06236/) (2017)
- [ECO: Efficient Convolutional Network for Online Video Understanding](https://mlsanity.com/paper/1804.09066/) (2018)
- [CDC: Convolutional-De-Convolutional Networks for Precise Temporal Action Localization in Untrimmed Videos](https://mlsanity.com/paper/1703.01515/) (2017)
- [Weakly Supervised Action Localization by Sparse Temporal Pooling Network](https://mlsanity.com/paper/1712.05080/) (2017)
- [TEINet: Towards an Efficient Architecture for Video Recognition](https://mlsanity.com/paper/1911.09435/) (2019)
- [W-TALC: Weakly-supervised Temporal Activity Localization and Classification](https://mlsanity.com/paper/1807.10418/) (2018)
- [AutoLoc: Weakly-supervised Temporal Action Localization](https://mlsanity.com/paper/1807.08333/) (2018)
- [Background Suppression Network for Weakly-supervised Temporal Action Localization](https://mlsanity.com/paper/1911.09963/) (2019)
- [Weakly-Supervised Action Localization by Generative Attention Modeling](https://mlsanity.com/paper/2003.12424/) (2020)
- [Weakly-supervised Action Localization with Background Modeling](https://mlsanity.com/paper/1908.06552/) (2019)
- [Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization](https://mlsanity.com/paper/2010.11594/) (2020)
- [STEP: Spatio-Temporal Progressive Learning for Video Action Detection](https://mlsanity.com/paper/1904.09288/) (2019)
- [Weakly-Supervised Action Localization with Expectation-Maximization Multi-Instance Learning](https://mlsanity.com/paper/2004.00163/) (2020)
- [Adversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization](https://mlsanity.com/paper/2007.06643/) (2020)
- [Context-Aware RCNN: A Baseline for Action Detection in Videos](https://mlsanity.com/paper/2007.09861/) (2020)
- [Marginalized Average Attentional Network for Weakly-Supervised Learning](https://mlsanity.com/paper/1905.08586/) (2019)

## Built on by (most cited first, 17 of 17)

- [ActionFormer: Localizing Moments of Actions with Transformers](https://mlsanity.com/paper/2202.07925/) (2022)
- [Dual Memory Units with Uncertainty Regulation for Weakly Supervised Video Anomaly Detection](https://mlsanity.com/paper/2302.05160/) (2023)
- [HR-Pro: Point-supervised Temporal Action Localization via Hierarchical Reliability Propagation](https://mlsanity.com/paper/2308.12608/) (2023)
- [Distilling Vision-Language Pre-training to Collaborate with Weakly-Supervised Temporal Action Localization](https://mlsanity.com/paper/2212.09335/) (2022)
- [Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach](https://mlsanity.com/paper/2312.14138/) (2023)
- [DDG-Net: Discriminability-Driven Graph Network for Weakly-supervised Temporal Action Localization](https://mlsanity.com/paper/2307.16415/) (2023)
- [Weakly-Supervised Temporal Action Localization by Progressive Complementary Learning](https://mlsanity.com/paper/2206.11011/) (2022)
- [Forcing the Whole Video as Background: An Adversarial Learning Strategy for Weakly Temporal Action Localization](https://mlsanity.com/paper/2207.06659/) (2022)
- [Slow Motion Matters: A Slow Motion Enhanced Network for Weakly Supervised Temporal Action Localization](https://mlsanity.com/paper/2211.11324/) (2022)
- [STAT: Towards Generalizable Temporal Action Localization](https://mlsanity.com/paper/2404.13311/) (2024)
- [Full-Stage Pseudo Label Quality Enhancement for Weakly-supervised Temporal Action Localization](https://mlsanity.com/paper/2407.08971/) (2024)
- [Convex Combination Consistency between Neighbors for Weakly-supervised Action Localization](https://mlsanity.com/paper/2205.00400/) (2022)
- [Weakly-Supervised Temporal Action Localization with Bidirectional Semantic Consistency Constraint](https://mlsanity.com/paper/2304.12616/) (2023)
- [A Hybrid Graph Network for Complex Activity Detection in Video](https://mlsanity.com/paper/2310.17493/) (2023)
- [Video-Specific Query-Key Attention Modeling for Weakly-Supervised Temporal Action Localization](https://mlsanity.com/paper/2305.04186/) (2023)
- [The Solution for Temporal Sound Localisation Task of ICCV 1st Perception Test Challenge 2023](https://mlsanity.com/paper/2407.02318/) (2024)
- [Boosting Point-supervised Temporal Action Localization via Text Refinement and Alignment](https://mlsanity.com/paper/2602.01257/) (2026)

## Abstract (arXiv)

Weakly-supervised temporal action localization (WTAL) in untrimmed videos has emerged as a practical but challenging task since only video-level labels are available. Existing approaches typically leverage off-the-shelf segment-level features, which suffer from spatial incompleteness and temporal incoherence, thus limiting their performance. In this paper, we tackle this problem from a new perspective by enhancing segment-level representations with a simple yet effective graph convolutional network, namely action complement graph network (ACGNet). It facilitates the current video segment to perceive spatial-temporal dependencies from others that potentially convey complementary clues, implicitly mitigating the negative effects caused by the two issues above. By this means, the segment-level features are more discriminative and robust to spatial-temporal variations, contributing to higher localization accuracies. More importantly, the proposed ACGNet works as a universal module that can be flexibly plugged into different WTAL frameworks, while maintaining the end-to-end training fashion. Extensive experiments are conducted on the THUMOS'14 and ActivityNet1.2 benchmarks, where the state-of-the-art results clearly demonstrate the superiority of the proposed approach.