Anna Khoreva (Post-Doc)

Publications

2024

  1. Conference paper
    D2
    “Adversarial Supervision Makes Layout-to-Image Diffusion Models Thrive,” in The Twelfth International Conference on Learning Representations (ICLR 2024), Vienna, Austria, 2024.

2023

  1. Conference paper
    D2
    “Intra-Source Style Augmentation for Improved Domain Generalization,” in 2023 IEEE Winter Conference on Applications of Computer Vision (WACV 2023), Waikoloa Village, HI, USA, 2023.
  2. Article
    D2
    “Intra- & Extra-Source Exemplar-Based Style Synthesis for Improved Domain Generalization,” International Journal of Computer Vision, 2023.
  3. Conference paper
    D2
    “Discovering Class-Specific GAN Controls for Semantic Image Synthesis,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2023), Vancouver, Canada, 2023.

2022

  1. Article
    D2
    “OASIS: Only Adversarial Supervision for Semantic Image Synthesis,” International Journal of Computer Vision, vol. 130, 2022.

2021

  1. Conference paper
    D2
    “You Only Need Adversarial Supervision for Semantic Image Synthesis,” in International Conference on Learning Representations (ICLR 2021), Vienna, Austria (Virtual), 2021.

2020

  1. Conference paper
    D2
    “A U-Net Based Discriminator for Generative Adversarial Networks,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, USA (Virtual), 2020.

2019

  1. Article
    D2
    “Lucid Data Dreaming for Video Object Segmentation,” International Journal of Computer Vision, vol. 127, no. 9, 2019.

2018

  1. Conference paper
    D2
    “Video Object Segmentation with Language Referring Expressions,” in Computer Vision - ACCV 2018, Perth, Australia, 2019.
  2. Conference paper
    D2
    “Learning to Refine Human Pose Estimation,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2018), Salt Lake City, UT, USA, 2018.

2017

  1. Conference paper
    D2
    “Learning Video Object Segmentation from Static Images,” in 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, USA, 2017.
  2. Conference paper
    D2
    “Simple Does It: Weakly Supervised Instance and Semantic Segmentation,” in 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, USA, 2017.
  3. Conference paper
    D2
    “Exploiting Saliency for Object Segmentation from Image Level Labels,” in 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, USA, 2017.
  4. Conference paper
    D2
    “Lucid Data Dreaming for Object Tracking,” in DAVIS Challenge on Video Object Segmentation 2017, Honolulu, HI, USA, 2017.
  5. Thesis
    D2IMPR-CS
    “Learning to Segment in Images and Videos with Different Forms of Supervision,” Universität des Saarlandes, Saarbrücken, 2017.
  6. Paper
    D2
    “Lucid Data Dreaming for Multiple Object Tracking,” 2017. [Online]. Available: http://arxiv.org/abs/1703.09554.

2016

  1. Conference paper
    D2
    “Weakly Supervised Object Boundaries,” in 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), Las Vegas, NV, USA, 2016.
  2. Conference paper
    D2
    “Improved Image Boundaries for Better Video Segmentation,” in Computer Vision -- ECCV 2016 Workshops, Amsterdam, The Netherlands, 2016.

2015

  1. Conference paper
    D2
    “Classifier Based Graph Construction for Video Segmentation,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015), Boston, MA USA, 2015.

2014

  1. Conference paper
    D2
    “Learning Must-Link Constraints for Video Segmentation Based on Spectral Clustering,” in Pattern Recognition (GCPR 2014), Münster, Germany, 2014.