# MSTR: Multi-Scale Transformer for End-to-End Human-Object Interaction Detection

arXiv: https://arxiv.org/abs/2203.14709 · HTML: https://mlsanity.com/paper/2203.14709/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 39 references that are in the map.
- First posted on arXiv 28 Mar 2022.

## Builds on (most cited first, 30 of 31)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [Deformable DETR: Deformable Transformers for End-to-End Object Detection](https://mlsanity.com/paper/2010.04159/) (2020)
- [Learning to Detect Human-Object Interactions](https://mlsanity.com/paper/1702.05448/) (2017)
- [Detecting and Recognizing Human-Object Interactions](https://mlsanity.com/paper/1704.07333/) (2017)
- [Visual Semantic Role Labeling](https://mlsanity.com/paper/1505.04474/) (2015)
- [HOTR: End-to-End Human-Object Interaction Detection with Transformers](https://mlsanity.com/paper/2104.13682/) (2021)
- [Learning Human-Object Interactions by Graph Parsing Neural Networks](https://mlsanity.com/paper/1808.07962/) (2018)
- [QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Information](https://mlsanity.com/paper/2103.05399/) (2021)
- [PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection](https://mlsanity.com/paper/1912.12898/) (2019)
- [End-to-End Human Object Interaction Detection with HOI Transformer](https://mlsanity.com/paper/2103.04503/) (2021)
- [Visual Compositional Learning for Human-Object Interaction Detection](https://mlsanity.com/paper/2007.12407/) (2020)
- [iCAN: Instance-Centric Attention Network for Human-Object Interaction Detection](https://mlsanity.com/paper/1808.10437/) (2018)
- [DRG: Dual Relation Graph for Human-Object Interaction Detection](https://mlsanity.com/paper/2008.11714/) (2020)
- [VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions](https://mlsanity.com/paper/2003.05541/) (2020)
- [Learning Human-Object Interaction Detection using Interaction Points](https://mlsanity.com/paper/2003.14023/) (2020)
- [Reformulating HOI Detection as Adaptive Set Prediction](https://mlsanity.com/paper/2103.05983/) (2021)
- [Detailed 2D-3D Joint Representation for Human-Object Interaction](https://mlsanity.com/paper/2004.08154/) (2020)
- [Pose-aware Multi-level Feature Network for Human Object Interaction Detection](https://mlsanity.com/paper/1909.08453/) (2019)
- [HOI Analysis: Integrating and Decomposing Human-Object Interaction](https://mlsanity.com/paper/2010.16219/) (2020)
- [PaStaNet: Toward Human Activity Knowledge Engine](https://mlsanity.com/paper/2004.00945/) (2020)
- [Detecting Human-Object Interactions with Action Co-occurrence Priors](https://mlsanity.com/paper/2007.08728/) (2020)
- [Glance and Gaze: Inferring Action-aware Points for One-Stage Human-Object Interaction Detection](https://mlsanity.com/paper/2104.05269/) (2021)
- [Deep Contextual Attention for Human-Object Interaction Detection](https://mlsanity.com/paper/1910.07721/) (2019)
- [Detecting Human-Object Interactions via Functional Generalization](https://mlsanity.com/paper/1904.03181/) (2019)
- [PnP-DETR: Towards Efficient Visual Analysis with Transformers](https://mlsanity.com/paper/2109.07036/) (2021)
- [Contextual Heterogeneous Graph Network for Human-Object Interaction Detection](https://mlsanity.com/paper/2010.10001/) (2020)
- [ConsNet: Learning Consistency Graph for Zero-Shot Human-Object Interaction Detection](https://mlsanity.com/paper/2008.06254/) (2020)
- [Visual Relationship Detection Using Part-and-Sum Transformers with Composite Queries](https://mlsanity.com/paper/2105.02170/) (2021)

## Built on by (most cited first, 30 of 34)

- [Exploring Predicate Visual Context in Detecting Human-Object Interactions](https://mlsanity.com/paper/2308.06202/) (2023)
- [RLIPv2: Fast Scaling of Relational Language-Image Pre-training](https://mlsanity.com/paper/2308.09351/) (2023)
- [ViPLO: Vision Transformer based Pose-Conditioned Self-Loop Graph for Human-Object Interaction Detection](https://mlsanity.com/paper/2304.08114/) (2023)
- [Relational Context Learning for Human-Object Interaction Detection](https://mlsanity.com/paper/2304.04997/) (2023)
- [Neural-Logic Human-Object Interaction Detection](https://mlsanity.com/paper/2311.09817/) (2023)
- [Exploring the Potential of Large Foundation Models for Open-Vocabulary HOI Detection](https://mlsanity.com/paper/2404.06194/) (2024)
- [Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion Deblurring](https://mlsanity.com/paper/2401.00027/) (2023)
- [Boosting Human-Object Interaction Detection with Text-to-Image Diffusion Model](https://mlsanity.com/paper/2305.12252/) (2023)
- [Category Query Learning for Human-Object Interaction Classification](https://mlsanity.com/paper/2303.14005/) (2023)
- [Learning from Observer Gaze:Zero-Shot Attention Prediction Oriented by Human-Object Interaction Recognition](https://mlsanity.com/paper/2405.09931/) (2024)
- [Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models](https://mlsanity.com/paper/2410.20155/) (2024)
- [Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning](https://mlsanity.com/paper/2303.01313/) (2023)
- [Groupwise Query Specialization and Quality-Aware Multi-Assignment for Transformer-based Visual Relationship Detection](https://mlsanity.com/paper/2403.17709/) (2024)
- [Agglomerative Transformer for Human-Object Interaction Detection](https://mlsanity.com/paper/2308.08370/) (2023)
- [Open-Vocabulary HOI Detection with Interaction-aware Prompt and Concept Calibration](https://mlsanity.com/paper/2508.03207/) (2025)
- [Weakly-Supervised HOI Detection from Interaction Labels Only and Language/Vision-Language Priors](https://mlsanity.com/paper/2303.05546/) (2023)
- [Exploiting CLIP for Zero-shot HOI Detection Requires Knowledge Distillation at Multiple Levels](https://mlsanity.com/paper/2309.05069/) (2023)
- [CycleHOI: Improving Human-Object Interaction Detection with Cycle Consistency of Detection and Generation](https://mlsanity.com/paper/2407.11433/) (2024)
- [A Review of Human-Object Interaction Detection](https://mlsanity.com/paper/2408.10641/) (2024)
- [Learning Human-Object Interaction as Groups](https://mlsanity.com/paper/2510.18357/) (2025)
- [DDS: Decoupled Dynamic Scene-Graph Generation Network](https://mlsanity.com/paper/2301.07666/) (2023)
- [Enhancing HOI Detection with Contextual Cues from Large Vision-Language Models](https://mlsanity.com/paper/2311.16475/) (2023)
- [SGC-Net: Stratified Granular Comparison Network for Open-Vocabulary HOI Detection](https://mlsanity.com/paper/2503.00414/) (2025)
- [Egocentric Human-Object Interaction Detection: A New Benchmark and Method](https://mlsanity.com/paper/2506.14189/) (2025)
- [RoHOI: Robustness Benchmark for Human-Object Interaction Detection](https://mlsanity.com/paper/2507.09111/) (2025)
- [Free-Form Composition Networks for Egocentric Action Recognition](https://mlsanity.com/paper/2307.06527/) (2023)
- [Geometric Features Enhanced Human-Object Interaction Detection](https://mlsanity.com/paper/2406.18691/) (2024)
- [VLM-HOI: Vision Language Models for Interpretable Human-Object Interaction Analysis](https://mlsanity.com/paper/2411.18038/) (2024)
- [Zero-shot HOI Detection with MLLM-based Detector-agnostic Interaction Recognition](https://mlsanity.com/paper/2602.15124/) (2026)
- [ScriptHOI: Learning Scripted State Transitions for Open-Vocabulary Human-Object Interaction Detection](https://mlsanity.com/paper/2605.05057/) (2026)

## Abstract (arXiv)

Human-Object Interaction (HOI) detection is the task of identifying a set of <human, object, interaction> triplets from an image. Recent work proposed transformer encoder-decoder architectures that successfully eliminated the need for many hand-designed components in HOI detection through end-to-end training. However, they are limited to single-scale feature resolution, providing suboptimal performance in scenes containing humans, objects and their interactions with vastly different scales and distances. To tackle this problem, we propose a Multi-Scale TRansformer (MSTR) for HOI detection powered by two novel HOI-aware deformable attention modules called Dual-Entity attention and Entity-conditioned Context attention. While existing deformable attention comes at a huge cost in HOI detection performance, our proposed attention modules of MSTR learn to effectively attend to sampling points that are essential to identify interactions. In experiments, we achieve the new state-of-the-art performance on two HOI detection benchmarks.