Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models

被引:0
|
作者
Haas, Rene [1 ]
Huberman-Spiegelglas, Inbar [2 ]
Mulayoff, Rotem [2 ]
Grasshof, Stella [1 ]
Brandt, Sami S. [1 ]
Michaeli, Tomer [2 ]
机构
[1] IT University of Copenhagen, Computer Science, Denmark
[2] Technion, Computer Science, Israel
关键词
Compilation and indexing terms; Copyright 2025 Elsevier Inc;
D O I
暂无
中图分类号
学科分类号
摘要
Computer vision - Diffusion - Generative adversarial networks - Spectrum analysis
引用
收藏
相关论文
共 50 条
  • [1] Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models
    Haas, René
    Huberman-Spiegelglas, Inbar
    Mulayoff, Rotem
    Graßhof, Stella
    Brandt, Sami S.
    Michaeli, Tomer
    arXiv, 2023,
  • [2] Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models
    Haas, Rene
    Huberman-Spiegelglas, Inbar
    Mulayoff, Rotem
    Grasshof, Stella
    Brandt, Sami S.
    Michaeli, Tomer
    2024 IEEE 18TH INTERNATIONAL CONFERENCE ON AUTOMATIC FACE AND GESTURE RECOGNITION, FG 2024, 2024,
  • [3] Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes
    Yang, Huiting
    Chai, Liangyu
    Wen, Qiang
    Zhao, Shuang
    Sun, Zixun
    He, Shengfeng
    2021 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, CVPR 2021, 2021, : 12172 - 12180
  • [4] Discovering Interpretable Latent Space Directions for 3D-Aware Image Generation
    Yang, Zhiyuan
    Zhang, Qingfu
    IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2024, 8 (03): : 2570 - 2580
  • [5] Self-Discovering Interpretable Diffusion Latent Directions for Responsible Text-to-Image Generation
    Li, Hang
    Shen, Chengzhi
    Torre, Philip
    Tresp, Volker
    Guo, Jindong
    2024 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2024, : 12006 - 12016
  • [6] Unleashing the Potential of the Semantic Latent Space in Diffusion Models for Image Dehazing
    Yang, Zizheng
    Yu, Hu
    Li, Bing
    Zhang, Jinghao
    Huang, Jie
    Zhao, Feng
    COMPUTER VISION-ECCV 2024, PT XLIV, 2025, 15102 : 371 - 389
  • [7] On the Semantic Latent Space of Diffusion-Based Text-to-Speech Models
    Varshaysky-Hassid, Miri
    Hirsch, Roy
    Cohen, Regev
    Golany, Tomer
    Freedman, Daniel
    Rivlin, Ehud
    PROCEEDINGS OF THE 62ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 2: SHORT PAPERS, 2024, : 246 - 255
  • [8] TRIBAC: Discovering Interpretable Clusters and Latent Structure in Graphs
    Chan, Jeffrey
    Leckie, Christopher
    Bailey, James
    Ramamohanarao, Kotagiri
    2014 IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), 2014, : 737 - 742
  • [9] Discovering Interpretable Medical Workflow Models
    Li, Jingyuan
    Yang, Sen
    Chen, Shuhong
    Tao, Fei
    Marsic, Ivan
    Burd, Randall S.
    2018 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI), 2018, : 437 - 439
  • [10] Discovering Density-Preserving Latent Space Walks in GANs for Semantic Image Transformations
    Li, Guanyue
    Liu, Yi
    Wei, Xiwen
    Zhang, Yang
    Wu, Si
    Xu, Yong
    Wong, Hau-San
    PROCEEDINGS OF THE 29TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA, MM 2021, 2021, : 1562 - 1570