Human-Object Interaction Detection via Weak Supervision
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Abstract (arXiv)
The goal of this paper is Human-object Interaction (HO-I) detection. HO-I detection aims to find interacting human-objects regions and classify their interaction from an image. Researchers obtain significant improvement in recent years by relying on strong HO-I alignment supervision from [5]. HO-I alignment supervision pairs humans with their interacted objects, and then aligns human-object pair(s) with their interaction categories. Since collecting such annotation is expensive, in this paper, we propose to detect HO-I without alignment supervision. We instead rely on image-level supervision that only enumerates existing interactions within the image without pointing where they happen. Our paper makes three contributions: i) We propose Align-Former, a visual-transformer based CNN that can detect HO-I with only image-level supervision. ii) Align-Former is equipped with HO-I align layer, that can learn to select appropriate targets to allow detector supervision. iii) We evaluate Align-Former on HICO-DET [5] and V-COCO [13], and show that Align-Former outperforms existing image-level supervised HO-I detectors by a large margin (4.71% mAP improvement from 16.14% to 20.85% on HICO-DET [5]).
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 27 of its 33 references that are in the map. First posted on arXiv 1 Dec 2021.
Builds on
27 of 33 references.
References · 27
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15 more
- 2017Convolutional Networks with Adaptive Inference Graphscited by 147
- 2021QPIC: Query-Based Pairwise Human-Object Interaction Detection with Image-Wide Contextual Informationcited by 147
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Built on by
Citing papers per year: 2023: 2; 2024: 2; 2025: 0; 2026: 1.
5 papers.
- 2023Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learningcited by 11
- 2023Exploiting CLIP for Zero-shot HOI Detection Requires Knowledge Distillation at Multiple Levelscited by 5
- 2024A Review of Human-Object Interaction Detectioncited by 5
- 2026Unleashing Multimodal Large Language Models for Training-free HOI Detection in the Wildcited by 1
- 2024FreeA: Human-object Interaction Detection using Free Annotation Labelscited by 0
- 2026Unleashing Multimodal Large Language Models for Training-free HOI Detection in the Wild15 Jul 2026
- 2024A Review of Human-Object Interaction Detection20 Aug 2024
- 2024FreeA: Human-object Interaction Detection using Free Annotation Labels4 Mar 2024
- 2023Exploiting CLIP for Zero-shot HOI Detection Requires Knowledge Distillation at Multiple Levels10 Sep 2023
- 2023Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning2 Mar 2023