Submission Details
The online submission for DGM4MICCAI is open until 19. June, 11:59 PM
Pacific Time.
Contributions must be submitted online through the OpenReview
submission system
We seek contributions that include, but are not limited to novel architectures, loss functions, and theoretical
developments for:
- Stable Diffusion Models
- Causal generative models
- Neural Cellular Automata
- GANs and Adversarial Learning
- Variational Auto-Encoder
- Disentanglement
- Flow
- Autoregressive models
- Multi-Modality and Cross-Modality linking
- Novel metrics and uncertainty estimates for performance assessment and
interpretability of
generative models
- Generative models under limited, sparse and noisy image inputs
- Supervised and Unsupervised Domain Adaptation, Transfer Learning and Multi-Task
Learning
- Segmentation, Detection, Synthesis, Reconstruction, Denoising, Supersampling,
Registration
- Image-to-Image translation for Synthetic Training Data Generation or Augmented
Reality
- Neural Rendering
We particularly welcome papers driven by the theme "MIC meets CAI".
Interesting novel applications of deep generative models in MIC and CAI beyond these
topics are
also welcome.
Workshop proceedings are published as part of Springer Nature's Lecture Notes in
Computer
Science (LNCS) series.
Manuscripts will be reviewed in double-blinded peer-review.
Please prepare your workshop papers according to the
MICCAI submission guidelines
(LNCS template, 8 pages maximum).
Supplementary material: Limited to multimedia content (e.g., videos in AVI, MP4 or WMV format).
PDF files may not be submitted as supplementary materials in 2026 unless authors are citing a paper that has not yet been published.
All supplementary material must be self-contained and zipped into a single file.
Reviewing Responsibility: At least one co-author must volunteer to review for
DGM4MICCAI
2026. The submission form will request the name and email address of
the qualified co-author
nominated for reviewing duties.
