Nikos Komodakis

papers

509

total citations

papers (11)

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

ICML 2025arXiv

citations

SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers

CVPR 2024arXiv

citations

DINO-Foresight: Looking into the Future with DINO

NEURIPS 2025arXiv

citations

Boosting Generative Image Modeling via Joint Image-Feature Synthesis

NEURIPS 2025arXiv

citations

QuEST: Quantized Embedding Space for Transferring Knowledge

ECCV 2020arXiv

citations

Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers

CVPR 2025arXiv

citations

Multi-Token Prediction Needs Registers

NEURIPS 2025arXiv

citations

ToNNO: Tomographic Reconstruction of a Neural Network’s Output for Weakly Supervised Segmentation of 3D Medical Images

CVPR 2024arXiv

citations

Nikos Komodakis

papers (11)

What to Hide from Your Students: Attention-Guided Masked Image Modeling

Learning Representations by Predicting Bags of Visual Words

OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers

DINO-Foresight: Looking into the Future with DINO

Boosting Generative Image Modeling via Joint Image-Feature Synthesis

QuEST: Quantized Embedding Space for Transferring Knowledge

Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers

Multi-Token Prediction Needs Registers

ToNNO: Tomographic Reconstruction of a Neural Network’s Output for Weakly Supervised Segmentation of 3D Medical Images

papers (11)

What to Hide from Your Students: Attention-Guided Masked Image Modeling

Learning Representations by Predicting Bags of Visual Words

OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers

DINO-Foresight: Looking into the Future with DINO

Boosting Generative Image Modeling via Joint Image-Feature Synthesis

QuEST: Quantized Embedding Space for Transferring Knowledge

Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers

Multi-Token Prediction Needs Registers

ToNNO: Tomographic Reconstruction of a Neural Network’s Output for Weakly Supervised Segmentation of 3D Medical Images