mlsanityData to 14 Oct 2026

Interactive Portrait Harmonization

arXiv 2203.08216 ↗First posted 15 Mar 2022cs.CVcited by 2

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Abstract (arXiv)

Current image harmonization methods consider the entire background as the guidance for harmonization. However, this may limit the capability for user to choose any specific object/person in the background to guide the harmonization. To enable flexible interaction between user and harmonization, we introduce interactive harmonization, a new setting where the harmonization is performed with respect to a selected region in the reference image instead of the entire background. A new flexible framework that allows users to pick certain regions of the background image and use it to guide the harmonization is proposed. Inspired by professional portrait harmonization users, we also introduce a new luminance matching loss to optimally match the color/luminance conditions between the composite foreground and select reference region. This framework provides more control to the image harmonization pipeline achieving visually pleasing portrait edits. Furthermore, we also introduce a new dataset carefully curated for validating portrait harmonization. Extensive experiments on both synthetic and real-world datasets show that the proposed approach is efficient and robust compared to previous harmonization baselines, especially for portraits. Project Webpage at hrefhttps://jeya-maria-jose.github.io/IPH-web/https://jeya-maria-jose.github.io/IPH-web/

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 21 of its 31 references that are in the map. First posted on arXiv 15 Mar 2022.

Builds on

21 of 31 references.

References · 21

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  3. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  4. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 2,010
  5. 2018Image Inpainting for Irregular Holes Using Partial Convolutionscited by 505
  6. 2020Multi-scale Interactive Network for Salient Object Detectioncited by 212
  7. 2017Deep Photo Style Transfercited by 168
  8. 2019Photorealistic Style Transfer via Wavelet Transformscited by 166
  9. 2019DoveNet: Deep Image Harmonization via Domain Verificationcited by 135
  10. 2018A Closed-form Solution to Photorealistic Image Stylizationcited by 133
  11. 2017Deep Image Harmonizationcited by 120
  12. 2019Improving the Harmony of the Composite Image by Spatial-Separated Attention Modulecited by 73
9 more
  1. 2021Region-aware Adaptive Instance Normalization for Image Harmonizationcited by 71
  2. 2018Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsingcited by 60
  3. 2021SSH: A Self-Supervised Framework for Image Harmonizationcited by 60
  4. 2020Foreground-aware Semantic Representations for Image Harmonizationcited by 53
  5. 2015Learning a Discriminative Model for the Perception of Realism in Composite Imagescited by 52
  6. 2020BargainNet: Background-Guided Domain Translation for Image Harmonizationcited by 52
  7. 2019Controllable Artistic Text Style Transfer via Shape-Matching GANcited by 45
  8. 2019What Else Can Fool Deep Learning? Addressing Color Constancy Errors on Deep Neural Network Performancecited by 37
  9. 2017Generative Partition Networks for Multi-Person Pose Estimationcited by 2

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Citing papers per year: 2023: 1; 2024: 1.

2 papers.