mlsanityData to 14 Oct 2026

Personalized Image Semantic Segmentation

arXiv 2107.13978 ↗First posted 24 Jul 2021cs.CVcited by 9

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Abstract (arXiv)

Semantic segmentation models trained on public datasets have achieved great success in recent years. However, these models didn't consider the personalization issue of segmentation though it is important in practice. In this paper, we address the problem of personalized image segmentation. The objective is to generate more accurate segmentation results on unlabeled personalized images by investigating the data's personalized traits. To open up future research in this area, we collect a large dataset containing various users' personalized images called PIS (Personalized Image Semantic Segmentation). We also survey some recent researches related to this problem and report their performance on our dataset. Furthermore, by observing the correlation among a user's personalized images, we propose a baseline method that incorporates the inter-image context when segmenting certain images. Extensive experiments show that our method outperforms the existing methods on the proposed dataset. The code and the PIS dataset will be made publicly available.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 43 of its 61 references that are in the map. First posted on arXiv 24 Jul 2021.

Builds on

43 of 61 references.

References · 43

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31 more
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Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 1; 2025: 5.

9 papers.

  1. 2022"This is my unicorn, Fluffy": Personalizing frozen vision-language representationscited by 95
  2. 2021PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Datasetcited by 9
  3. 2024Cross-Architecture Auxiliary Feature Space Translation for Efficient Few-Shot Personalized Object Detectioncited by 5
  4. 2025MOCHA: Multi-modal Objects-aware Cross-arcHitecture Alignmentcited by 2
  5. 2023PGA: Personalizing Grasping Agents with Single Human-Robot Interactioncited by 0
  6. 2025Deeply Dual Supervised learning for melanoma recognitioncited by 0
  7. 2025Edge Detection for Organ Boundaries via Top Down Refinement and SubPixel Upsamplingcited by 0
  8. 2025DualResolution Residual Architecture with Artifact Suppression for Melanocytic Lesion Segmentationcited by 0
  9. 2025VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagationcited by 0