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Parsing R-CNN for Instance-Level Human Analysis

arXiv 1811.12596 ↗First posted 30 Nov 2018cs.CVcited by 53

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Abstract (arXiv)

Instance-level human analysis is common in real-life scenarios and has multiple manifestations, such as human part segmentation, dense pose estimation, human-object interactions, etc. Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance. In this paper, we present an end-to-end pipeline for solving the instance-level human analysis, named Parsing R-CNN. It processes a set of human instances simultaneously through comprehensive considering the characteristics of region-based approach and the appearance of a human, thus allowing representing the details of instances. Parsing R-CNN is very flexible and efficient, which is applicable to many issues in human instance analysis. Our approach outperforms all state-of-the-art methods on CIHP (Crowd Instance-level Human Parsing), MHP v2.0 (Multi-Human Parsing) and DensePose-COCO datasets. Based on the proposed Parsing R-CNN, we reach the 1st place in the COCO 2018 Challenge DensePose Estimation task. Code and models are public available.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Nov 2018.

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Citing papers per year: 2021: 13; 2022: 15; 2023: 13; 2024: 6; 2025: 3; 2026: 3.

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  1. 2023Semantic-SAM: Segment and Recognize Anything at Any Granularitycited by 185
  2. 2023PACO: Parts and Attributes of Common Objectscited by 146
  3. 2024Controllable Generation with Text-to-Image Diffusion Models: A Surveycited by 82
  4. 2021Part-aware Panoptic Segmentationcited by 56
  5. 2023Going Denser with Open-Vocabulary Part Segmentationcited by 51
  6. 2022Panoptic-PartFormer: Learning a Unified Model for Panoptic Part Segmentationcited by 38
  7. 2021Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsingcited by 31
  8. 2025MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentationcited by 28
  9. 20223D Segmentation of Humans in Point Clouds with Synthetic Datacited by 24
  10. 2023PanopticPartFormer++: A Unified and Decoupled View for Panoptic Part Segmentationcited by 19
  11. 2023Deep Learning Technique for Human Parsing: A Survey and Outlookcited by 18
  12. 2022Fashionformer: A simple, Effective and Unified Baseline for Human Fashion Segmentation and Recognitioncited by 16
38 more
  1. 2024PartGLEE: A Foundation Model for Recognizing and Parsing Any Objectscited by 15
  2. 2022AIParsing: Anchor-free Instance-level Human Parsingcited by 14
  3. 2021Quality-Aware Network for Human Parsingcited by 13
  4. 2021Discovering Relationships between Object Categories via Universal Canonical Mapscited by 13
  5. 2023Semantic Human Parsing via Scalable Semantic Transfer over Multiple Label Domainscited by 11
  6. 2021UltraPose: Synthesizing Dense Pose with 1 Billion Points by Human-body Decoupling 3D Modelcited by 9
  7. 2023What Decreases Editing Capability? Domain-Specific Hybrid Refinement for Improved GAN Inversioncited by 7
  8. 2023Image is All You Need to Empower Large-scale Diffusion Models for In-Domain Generationcited by 7
  9. 2022Multi-task Fusion for Efficient Panoptic-Part Segmentationcited by 6
  10. 2022KTN: Knowledge Transfer Network for Learning Multi-person 2D-3D Correspondencescited by 5
  11. 2021End-to-end One-shot Human Parsingcited by 4
  12. 2021Multi-initialization Optimization Network for Accurate 3D Human Pose and Shape Estimationcited by 4
  13. 2022LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Spacecited by 4
  14. 2024Task-aligned Part-aware Panoptic Segmentation through Joint Object-Part Representationscited by 4
  15. 2024CALICO: Part-Focused Semantic Co-Segmentation with Large Vision-Language Modelscited by 4
  16. 2021Temporal Consistency Loss for High Resolution Textured and Clothed 3DHuman Reconstruction from Monocular Videocited by 3
  17. 2021Quality-Aware Network for Face Parsingcited by 3
  18. 2022Describe me if you can! Characterized Instance-level Human Parsingcited by 3
  19. 2022KE-RCNN: Unifying Knowledge based Reasoning into Part-level Attribute Parsingcited by 3
  20. 2022RepParser: End-to-End Multiple Human Parsing with Representative Partscited by 3
  21. 2023UniParser: Multi-Human Parsing with Unified Correlation Representation Learningcited by 3
  22. 2024Frequency-based Matcher for Long-tailed Semantic Segmentationcited by 3
  23. 2021Clicking Matters:Towards Interactive Human Parsingcited by 2
  24. 2022Parsing Objects at a Finer Granularity: A Surveycited by 2
  25. 2023Single-stage Multi-human Parsing via Point Sets and Center-based Offsetscited by 2
  26. 2023JPPF: Multi-task Fusion for Consistent Panoptic-Part Segmentationcited by 2
  27. 2025Scale-Aware Pre-Training for Human-Centric Visual Perception: Enabling Lightweight and Generalizable Modelscited by 2
  28. 2021Semantic-guided Automatic Natural Image Matting with Trimap Generation Network and Light-weight Non-local Attentioncited by 1
  29. 2021Technical Report: Disentangled Action Parsing Networks for Accurate Part-level Action Parsingcited by 1
  30. 2022Direct Dense Pose Estimationcited by 1
  31. 2022SGM-Net: Semantic Guided Matting Netcited by 1
  32. 2022TIVE: A Toolbox for Identifying Video Instance Segmentation Errorscited by 1
  33. 2023Deep Learning for Human Parsing: A Surveycited by 1
  34. 2026SAM-pose2seg: Pose-Guided Human Instance Segmentation in Crowdscited by 1
  35. 2021Nondiscriminatory Treatment: a straightforward framework for multi-human parsingcited by 0
  36. 2022UV R-CNN: Stable and Efficient Dense Human Pose Estimationcited by 0
  37. 2023CIParsing: Unifying Causality Properties into Multiple Human Parsingcited by 0
  38. 2024Automated Sperm Morphology Analysis Based on Instance-Aware Part Segmentationcited by 0

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