# Attention-Aware Compositional Network for Person Re-identification

arXiv: https://arxiv.org/abs/1805.03344 · HTML: https://mlsanity.com/paper/1805.03344/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 May 2018.

## Built on by (most cited first, 30 of 50)

- [Attention Mechanisms in Computer Vision: A Survey](https://mlsanity.com/paper/2111.07624/) (2021)
- [Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer](https://mlsanity.com/paper/2106.04095/) (2021)
- [Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification](https://mlsanity.com/paper/2108.08728/) (2021)
- [Semantically Self-Aligned Network for Text-to-Image Part-aware Person Re-identification](https://mlsanity.com/paper/2107.12666/) (2021)
- [UniHCP: A Unified Model for Human-Centric Perceptions](https://mlsanity.com/paper/2303.02936/) (2023)
- [Semantics for Robotic Mapping, Perception and Interaction: A Survey](https://mlsanity.com/paper/2101.00443/) (2021)
- [Attention, please! A survey of Neural Attention Models in Deep Learning](https://mlsanity.com/paper/2103.16775/) (2021)
- [Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective](https://mlsanity.com/paper/2104.11536/) (2021)
- [Feature Erasing and Diffusion Network for Occluded Person Re-Identification](https://mlsanity.com/paper/2112.08740/) (2021)
- [TransMatcher: Deep Image Matching Through Transformers for Generalizable Person Re-identification](https://mlsanity.com/paper/2105.14432/) (2021)
- [Feature Completion for Occluded Person Re-Identification](https://mlsanity.com/paper/2106.12733/) (2021)
- [SDPL: Shifting-Dense Partition Learning for UAV-View Geo-Localization](https://mlsanity.com/paper/2403.04172/) (2024)
- [Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks](https://mlsanity.com/paper/2207.01580/) (2022)
- [Towards Discriminative Representation Learning for Unsupervised Person Re-identification](https://mlsanity.com/paper/2108.03439/) (2021)
- [Quality-aware Part Models for Occluded Person Re-identification](https://mlsanity.com/paper/2201.00107/) (2022)
- [Cloning Outfits from Real-World Images to 3D Characters for Generalizable Person Re-Identification](https://mlsanity.com/paper/2204.02611/) (2022)
- [Uncertainty-aware Clustering for Unsupervised Domain Adaptive Object Re-identification](https://mlsanity.com/paper/2108.09682/) (2021)
- [Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends](https://mlsanity.com/paper/2202.13121/) (2022)
- [Occluded Person Re-Identification with Deep Learning: A Survey and Perspectives](https://mlsanity.com/paper/2311.00603/) (2023)
- [Learning Multi-Attention Context Graph for Group-Based Re-Identification](https://mlsanity.com/paper/2104.14236/) (2021)
- [Person Re-identification via Attention Pyramid](https://mlsanity.com/paper/2108.05340/) (2021)
- [Deep Learning-based Occluded Person Re-identification: A Survey](https://mlsanity.com/paper/2207.14452/) (2022)
- [Other Tokens Matter: Exploring Global and Local Features of Vision Transformers for Object Re-Identification](https://mlsanity.com/paper/2404.14985/) (2024)
- [G2DA: Geometry-Guided Dual-Alignment Learning for RGB-Infrared Person Re-Identification](https://mlsanity.com/paper/2106.07853/) (2021)
- [Keypoint Message Passing for Video-based Person Re-Identification](https://mlsanity.com/paper/2111.08279/) (2021)
- [Style Interleaved Learning for Generalizable Person Re-identification](https://mlsanity.com/paper/2207.03132/) (2022)
- [Identity-aware Feature Decoupling Learning for Clothing-change Person Re-identification](https://mlsanity.com/paper/2501.05851/) (2025)
- [Decentralised Person Re-Identification with Selective Knowledge Aggregation](https://mlsanity.com/paper/2110.11384/) (2021)
- [Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification](https://mlsanity.com/paper/2102.09321/) (2021)
- [A Brief Survey on Person Recognition at a Distance](https://mlsanity.com/paper/2212.08969/) (2022)

## Abstract (arXiv)

Person re-identification (ReID) is to identify pedestrians observed from different camera views based on visual appearance. It is a challenging task due to large pose variations, complex background clutters and severe occlusions. Recently, human pose estimation by predicting joint locations was largely improved in accuracy. It is reasonable to use pose estimation results for handling pose variations and background clutters, and such attempts have obtained great improvement in ReID performance. However, we argue that the pose information was not well utilized and hasn't yet been fully exploited for person ReID. In this work, we introduce a novel framework called Attention-Aware Compositional Network (AACN) for person ReID. AACN consists of two main components: Pose-guided Part Attention (PPA) and Attention-aware Feature Composition (AFC). PPA is learned and applied to mask out undesirable background features in pedestrian feature maps. Furthermore, pose-guided visibility scores are estimated for body parts to deal with part occlusion in the proposed AFC module. Extensive experiments with ablation analysis show the effectiveness of our method, and state-of-the-art results are achieved on several public datasets, including Market-1501, CUHK03, CUHK01, SenseReID, CUHK03-NP and DukeMTMC-reID.