A Compositionally Architecture for Perceptual Feature Grouping. - Björn Ommer; Joachim M. Buhmann (EMMCVPR, 2003)

Object Categorization by Compositional Graphical Models. - Björn Ommer; Joachim M. Buhmann (EMMCVPR, 2005)

Learning Top-Down Grouping of Compositional Hierarchies for Recognition. - Björn Ommer; Michael Sauter; Joachim M. Buhmann (CVPR Workshops, 2006)

Exploiting Low-Level Image Segmentation for Object Recognition. - Volker Roth 001; Björn Ommer (DAGM-Symposium, 2006)

Learning Compositional Categorization Models. - Björn Ommer; Joachim M. Buhmann (ECCV (3), 2006)

Learning the Compositional Nature of Visual Objects. - Björn Ommer; Joachim M. Buhmann (CVPR, 2007)

Compositional Object Recognition, Segmentation, and Tracking in Video. - Björn Ommer; Joachim M. Buhmann (EMMCVPR, 2007)

Learning the Compositional Nature of Objects for Visual Recognition. - Björn Ommer (2007)

Multi-scale object detection by clustering lines. - Björn Ommer; Jitendra Malik (ICCV, 2009)

Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera. - Björn Ommer; Theodor Mader; Joachim M. Buhmann (Int. J. Comput. Vis., 2009)

Efficient Clustering Earth Mover's Distance. - Jenny Wagner; Björn Ommer (ACCV (2), 2010)

Recognition and Analysis of Objects in Medieval Images. - Pradeep Yarlagadda; Antonio Monroy; Bernd Carqué; Björn Ommer (ACCV Workshops (2), 2010)

Voting by Grouping Dependent Parts. - Pradeep Yarlagadda; Antonio Monroy; Björn Ommer (ECCV (5), 2010)

Learning the Compositional Nature of Visual Object Categories for Recognition. - Björn Ommer; Joachim M. Buhmann (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

Contour-based object detection. - Joseph Schlecht; Björn Ommer (BMVC, 2011)

Top-down analysis of low-level object relatedness leading to semantic understanding of medieval image collections. - Pradeep Yarlagadda; Antonio Monroy; Bernd Carqué; Björn Ommer (Computer Vision and Image Analysis of Art, 2011)

Video parsing for abnormality detection. - Borislav Antic; Björn Ommer (ICCV, 2011)

Reconstructing the drawing process of reproductions from medieval images. - Antonio Monroy; Bernd Carqué; Björn Ommer (ICIP, 2011)

Beyond straight lines - Object detection using curvature. - Antonio Monroy; Angela Eigenstetter; Björn Ommer (ICIP, 2011)

Detecting gestures in medieval images. - Joseph Schlecht; Bernd Carqué; Björn Ommer (ICIP, 2011)

Robust Multiple-Instance Learning with Superbags. - Borislav Antic; Björn Ommer (ACCV (2), 2012)

Max-Margin Regularization for Reducing Accidentalness in Chamfer Matching. - Angela Eigenstetter; Pradeep Krishna Yarlagadda; Björn Ommer (ACCV (1), 2012)

Learning Discriminative Chamfer Regularization. - Pradeep Yarlagadda; Angela Eigenstetter; Björn Ommer (BMVC, 2012)

Shaping Art with Art: Morphological Analysis for Investigating Artistic Reproductions. - Juan Antonio Monroy Kuhn; Peter Bell 007; Björn Ommer (ECCV Workshops (1), 2012)

Beyond Bounding-Boxes: Learning Object Shape by Model-Driven Grouping. - Antonio Monroy; Björn Ommer (ECCV (3), 2012)

From Meaningful Contours to Discriminative Object Shape. - Pradeep Yarlagadda; Björn Ommer (ECCV (1), 2012)

Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity. - Angela Eigenstetter; Björn Ommer (NIPS, 2012)

The Role of Shape in Visual Recognition. - Björn Ommer (Shape Perception in Human and Computer Vision, 2013)

Less Is More: Video Trimming for Action Recognition. - Borislav Antic; Timo Milbich; Björn Ommer (ICCV Workshops, 2013)

Randomized Max-Margin Compositions for Visual Recognition. - Angela Eigenstetter; Masato Takami; Björn Ommer (CVPR, 2014)

Learning Latent Constituents for Recognition of Group Activities in Video. - Borislav Antic; Björn Ommer (ECCV (1), 2014)

Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. - Melih Kandemir; José C. Rubio; Ute Schmidt; Christian Wojek; Johannes Welbl; Björn Ommer; Fred A. Hamprecht (MICCAI (2), 2014)

An Approach to Large Scale Interactive Retrieval of Cultural Heritage. - Masato Takami; Peter Bell 007; Björn Ommer (GCH, 2014)

Offline learning of prototypical negatives for efficient online Exemplar SVM. - Masato Takami; Peter Bell 007; Björn Ommer (WACV, 2014)

Morphological analysis for investigating artistic images. - Antonio Monroy; Peter Bell 007; Björn Ommer (Image Vis. Comput., 2014)

Regularizing max-margin exemplars by reconstruction and generative models. - José C. Rubio; Björn Ommer (CVPR, 2015)

Per-Sample Kernel Adaptation for Visual Recognition and Grouping. - Borislav Antic; Björn Ommer (ICCV, 2015)

Spatiotemporal Parsing of Motor Kinematics for Assessing Stroke Recovery. - Borislav Antic; Uta Büchler; Anna-Sophia Wahl; Martin E. Schwab; Björn Ommer (MICCAI (3), 2015)

Spatio-temporal Video Parsing for Abnormality Detection. - Borislav Antic; Björn Ommer (CoRR, 2015)

Beyond the Sum of Parts: Voting with Groups of Dependent Entities. - Pradeep Yarlagadda; Björn Ommer (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Generative regularization with latent topics for discriminative object recognition. - José C. Rubio; Angela Eigenstetter; Björn Ommer (Pattern Recognit., 2015)

CliqueCNN: Deep Unsupervised Exemplar Learning. - Miguel Ángel Bautista 001; Artsiom Sanakoyeu; Ekaterina Tikhoncheva; Björn Ommer (NIPS, 2016)

Deep Unsupervised Similarity Learning Using Partially Ordered Sets. - Miguel Ángel Bautista 001; Artsiom Sanakoyeu; Björn Ommer (CVPR, 2017)

LSTM Self-Supervision for Detailed Behavior Analysis. - Biagio Brattoli; Uta Büchler; Anna-Sophia Wahl; Martin E. Schwab; Björn Ommer (CVPR, 2017)

Deep Semantic Feature Matching. - Nikolai Ufer; Björn Ommer (CVPR, 2017)

Learning Where to Drive by Watching Others. - Miguel Ángel Bautista 001; Patrick Fuchs; Björn Ommer (GCPR, 2017)

Unsupervised Video Understanding by Reconciliation of Posture Similarities. - Timo Milbich; Miguel Ángel Bautista 001; Ekaterina Sutter; Björn Ommer (ICCV, 2017)

Self-Supervised Learning of Pose Embeddings from Spatiotemporal Relations in Videos. - Ömer Sümer; Tobias Dencker; Björn Ommer (ICCV, 2017)

A Variational U-Net for Conditional Appearance and Shape Generation. - Patrick Esser; Ekaterina Sutter; Björn Ommer (CVPR, 2018)

X-GAN: Improving Generative Adversarial Networks with ConveX Combinations. - Oliver Blum; Biagio Brattoli; Björn Ommer (GCPR, 2018)

Cross and Learn: Cross-Modal Self-supervision. - Nawid Sayed; Biagio Brattoli; Björn Ommer (GCPR, 2018)

Der ferne Blick. Bildkorpora und Computer Vision in den Geistes- und Kulturwissenschaften - Stand - Visionen - Implikationen. - Simon Donig; Siegfried Handschuh; Erik Radisch; Malte Rehbein; Canan Hastik; Hubertus Kohle; Björn Ommer (DHd, 2018)

Beyond Image Search: Computer Vision in Western Art History. - Leonardo Laurence Impett; Peter Bell 007; Benoit Seguin; Björn Ommer (DH, 2018)

Urban Art in a Digital Context: A Computer-Based Evaluation of Street Art and Graffiti Writing. - Sabine Lang; Björn Ommer (DH, 2018)

Improving Spatiotemporal Self-supervision by Deep Reinforcement Learning. - Uta Büchler; Biagio Brattoli; Björn Ommer (ECCV (15), 2018)

Towards Learning a Realistic Rendering of Human Behavior. - Patrick Esser; Johannes Haux; Timo Milbich; Björn Ommer (ECCV Workshops (2), 2018)

Reflecting on How Artworks Are Processed and Analyzed by Computer Vision. - Sabine Lang; Björn Ommer (ECCV Workshops (2), 2018)

A Style-Aware Content Loss for Real-Time HD Style Transfer. - Artsiom Sanakoyeu; Dmytro Kotovenko; Sabine Lang; Björn Ommer (ECCV (8), 2018)

Learning to Forecast Pedestrian Intention from Pose Dynamics. - Omair Ghori; Radek Mackowiak; Miguel Ángel Bautista 001; Niklas Beuter; Lucas Drumond; Ferran Diego; Björn Ommer (Intelligent Vehicles Symposium, 2018)

Attesting similarity: Supporting the organization and study of art image collections with computer vision. - Sabine Lang; Björn Ommer (Digit. Scholarsh. Humanit., 2018)

Deep unsupervised learning of visual similarities. - Artsiom Sanakoyeu; Miguel Ángel Bautista 001; Björn Ommer (Pattern Recognit., 2018)

A Content Transformation Block for Image Style Transfer. - Dmytro Kotovenko; Artsiom Sanakoyeu; Pingchuan Ma 006; Sabine Lang; Björn Ommer (CVPR, 2019)

Unsupervised Part-Based Disentangling of Object Shape and Appearance. - Dominik Lorenz; Leonard Bereska; Timo Milbich; Björn Ommer (CVPR, 2019)

Divide and Conquer the Embedding Space for Metric Learning. - Artsiom Sanakoyeu; Vadim Tschernezki; Uta Büchler; Björn Ommer (CVPR, 2019)

Weakly Supervised Learning of Dense Semantic Correspondences and Segmentation. - Nikolai Ufer; Kam To Lui; Katja Schwarz; Paul Warkentin; Björn Ommer (GCPR, 2019)

MIC: Mining Interclass Characteristics for Improved Metric Learning. - Biagio Brattoli; Karsten Roth; Björn Ommer (ICCV, 2019)

Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis. - Patrick Esser; Johannes Haux; Björn Ommer (ICCV, 2019)

Content and Style Disentanglement for Artistic Style Transfer. - Dmytro Kotovenko; Artsiom Sanakoyeu; Sabine Lang; Björn Ommer (ICCV, 2019)

Multi-Scale Convolutions for Learning Context Aware Feature Representations. - Nikolai Ufer; Kam To Lui; Katja Schwarz; Paul Warkentin; Björn Ommer (CoRR, 2019)

Unsupervised Magnification of Posture Deviations Across Subjects. - Michael Dorkenwald; Uta Büchler; Björn Ommer (CVPR, 2020)

A Disentangling Invertible Interpretation Network for Explaining Latent Representations. - Patrick Esser; Robin Rombach; Björn Ommer (CVPR, 2020)

PADS: Policy-Adapted Sampling for Visual Similarity Learning. - Karsten Roth; Timo Milbich; Björn Ommer (CVPR, 2020)

Unsupervised Part Discovery by Unsupervised Disentanglement. - Sandro Braun; Patrick Esser; Björn Ommer (GCPR, 2020)

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning. - Timo Milbich; Karsten Roth; Homanga Bharadhwaj; Samarth Sinha; Yoshua Bengio; Björn Ommer; Joseph Paul Cohen (ECCV (8), 2020)

Making Sense of CNNs: Interpreting Deep Representations and Their Invariances with INNs. - Robin Rombach; Patrick Esser; Björn Ommer (ECCV (17), 2020)

Object Retrieval and Localization in Large Art Collections Using Deep Multi-style Feature Fusion and Iterative Voting. - Nikolai Ufer; Sabine Lang; Björn Ommer (ECCV Workshops (2), 2020)

Revisiting Training Strategies and Generalization Performance in Deep Metric Learning. - Karsten Roth; Timo Milbich; Samarth Sinha; Prateek Gupta; Björn Ommer; Joseph Paul Cohen (ICML, 2020)

Network-to-Network Translation with Conditional Invertible Neural Networks. - Robin Rombach; Patrick Esser; Björn Ommer (NeurIPS, 2020)

Learning to Correct Overexposed and Underexposed Photos. - Mahmoud Afifi; Konstantinos G. Derpanis; Björn Ommer; Michael S. Brown (CoRR, 2020)

Network Fusion for Content Creation with Conditional INNs. - Robin Rombach; Patrick Esser; Björn Ommer (CoRR, 2020)

Making Sense of CNNs: Interpreting Deep Representations & Their Invariances with INNs. - Robin Rombach; Patrick Esser; Björn Ommer (CoRR, 2020)

S2SD: Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. - Karsten Roth; Timo Milbich; Björn Ommer; Joseph Paul Cohen; Marzyeh Ghassemi (CoRR, 2020)

A Note on Data Biases in Generative Models. - Patrick Esser; Robin Rombach; Björn Ommer (CoRR, 2020)

uBAM: Unsupervised Behavior Analysis and Magnification using Deep Learning. - Biagio Brattoli; Uta Büchler; Michael Dorkenwald; Philipp Reiser; Linard Filli; Fritjof Helmchen; Anna-Sophia Wahl; Björn Ommer (CoRR, 2020)

Unsupervised representation learning by discovering reliable image relations. - Timo Milbich; Omair Ghori; Ferran Diego; Björn Ommer (Pattern Recognit., 2020)

Unsupervised View-Invariant Human Posture Representation. - Faegheh Sardari; Björn Ommer; Majid Mirmehdi (BMVC, 2021)

Learning Multi-Scale Photo Exposure Correction. - Mahmoud Afifi; Konstantinos G. Derpanis; Björn Ommer; Michael S. Brown (CVPR, 2021)

Understanding Object Dynamics for Interactive Image-to-Video Synthesis. - Andreas Blattmann; Timo Milbich; Michael Dorkenwald; Björn Ommer (CVPR, 2021)

Behavior-Driven Synthesis of Human Dynamics. - Andreas Blattmann; Timo Milbich; Michael Dorkenwald; Björn Ommer (CVPR, 2021)

Stochastic Image-to-Video Synthesis Using cINNs. - Michael Dorkenwald; Timo Milbich; Andreas Blattmann; Robin Rombach; Konstantinos G. Derpanis; Björn Ommer (CVPR, 2021)

Taming Transformers for High-Resolution Image Synthesis. - Patrick Esser; Robin Rombach; Björn Ommer (CVPR, 2021)

Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes. - Dmytro Kotovenko; Matthias Wright; Arthur Heimbrecht; Björn Ommer (CVPR, 2021)

SLIM: Self-Supervised LiDAR Scene Flow and Motion Segmentation. - Stefan Andreas Baur; David Josef Emmerichs; Frank Moosmann; Peter Pinggera; Björn Ommer; Andreas Geiger 001 (ICCV, 2021)

iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis. - Andreas Blattmann; Timo Milbich; Michael Dorkenwald; Björn Ommer (ICCV, 2021)

Geometry-Free View Synthesis: Transformers and no 3D Priors. - Robin Rombach; Patrick Esser; Björn Ommer (ICCV, 2021)

Shape or Texture: Understanding Discriminative Features in CNNs. - Md. Amirul Islam; Matthew Kowal; Patrick Esser; Sen Jia 002; Björn Ommer; Konstantinos G. Derpanis; Neil D. B. Bruce (ICLR, 2021)

Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. - Karsten Roth; Timo Milbich; Björn Ommer; Joseph Paul Cohen; Marzyeh Ghassemi (ICML, 2021)

VelocityNet: Motion-Driven Feature Aggregation for 3D Object Detection in Point Cloud Sequences. - David Emmerichs; Peter Pinggera; Björn Ommer (ICRA, 2021)

ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis. - Patrick Esser; Robin Rombach; Andreas Blattmann; Björn Ommer (NeurIPS, 2021)

Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning. - Timo Milbich; Karsten Roth; Samarth Sinha; Ludwig Schmidt; Marzyeh Ghassemi; Björn Ommer (NeurIPS, 2021)

High-Resolution Complex Scene Synthesis with Transformers. - Manuel Jahn; Robin Rombach; Björn Ommer (CoRR, 2021)

Transforming Information Into Knowledge: How Computational Methods Reshape Art History. - Sabine Lang; Björn Ommer (Digit. Humanit. Q., 2021)

Unsupervised behaviour analysis and magnification (uBAM) using deep learning. - Biagio Brattoli; Uta Büchler; Michael Dorkenwald; Philipp Reiser; Linard Filli; Fritjof Helmchen; Anna-Sophia Wahl; Björn Ommer (Nat. Mach. Intell., 2021)

Unsupervised behaviour analysis and magnification (uBAM) using deep learning Dataset. - Biagio Brattoli; Uta Büchler; Michael Dorkenwald; Philipp Reiser; Linard Filli; Fritjof Helmchen; Anna-Sophia Wahl; Björn Ommer (Zenodo, 2021)

Maximizing Mutual Shape Information. - Md. Amirul Islam; Matthew Kowal; Patrick Esser; Björn Ommer; Konstantinos G. Derpanis; Neil D. B. Bruce (BMVC, 2022)

High-Resolution Image Synthesis with Latent Diffusion Models. - Robin Rombach; Andreas Blattmann; Dominik Lorenz; Patrick Esser; Björn Ommer (CVPR, 2022)

ArtFID: Quantitative Evaluation of Neural Style Transfer. - Matthias Wright; Björn Ommer (GCPR, 2022)

Retrieval-Augmented Diffusion Models. - Andreas Blattmann; Robin Rombach; Kaan Oktay; Jonas Müller; Björn Ommer (NeurIPS, 2022)

Retrieval-Augmented Diffusion Models. - Andreas Blattmann; Robin Rombach; Kaan Oktay; Björn Ommer (CoRR, 2022)

Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Models. - Robin Rombach; Andreas Blattmann; Björn Ommer (CoRR, 2022)

Sharing Matters for Generalization in Deep Metric Learning. - Timo Milbich; Karsten Roth; Biagio Brattoli; Björn Ommer (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Improving Deep Metric Learning by Divide and Conquer. - Artsiom Sanakoyeu; Pingchuan Ma 006; Vadim Tschernezki; Björn Ommer (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Cross-Image-Attention for Conditional Embeddings in Deep Metric Learning. - Dmytro Kotovenko; Pingchuan Ma 006; Timo Milbich; Björn Ommer (CVPR, 2023)

SceneGenie: Scene Graph Guided Diffusion Models for Image Synthesis. - Azade Farshad; Yousef Yeganeh; Yu Chi 002; Chengzhi Shen; Björn Ommer; Nassir Navab (ICCV (Workshops), 2023)

Boosting Latent Diffusion with Flow Matching. - Johannes S. Fischer; Ming Gui; Pingchuan Ma 006; Nick Stracke; Stefan Andreas Baumann; Björn Ommer (CoRR, 2023)

Guided Diffusion from Self-Supervised Diffusion Features. - Vincent Tao Hu; Yunlu Chen; Mathilde Caron; Yuki M. Asano; Cees G. M. Snoek; Björn Ommer (CoRR, 2023)

Motion Flow Matching for Human Motion Synthesis and Editing. - Vincent Tao Hu; Wenzhe Yin; Pingchuan Ma 006; Yunlu Chen; Basura Fernando; Yuki M. Asano; Efstratios Gavves; Pascal Mettes; Björn Ommer; Cees G. M. Snoek (CoRR, 2023)

Flow Matching for Conditional Text Generation in a Few Sampling Steps. - Vincent Tao Hu; Di Wu; Yuki Markus Asano; Pascal Mettes; Basura Fernando; Björn Ommer; Cees Snoek (EACL (2), 2024)

ZigMa: A DiT-style Zigzag Mamba Diffusion Model. - Vincent Tao Hu; Stefan Andreas Baumann; Ming Gui; Olga Grebenkova; Pingchuan Ma 006; Johannes S. Fischer; Björn Ommer (ECCV (21), 2024)

WaSt-3D: Wasserstein-2 Distance for Scene-to-Scene Stylization on 3D Gaussians. - Dmytro Kotovenko; Olga Grebenkova; Nikolaos Sarafianos; Avinash Paliwal; Pingchuan Ma 006; Omid Poursaeed; Sreyas Mohan; Yuchen Fan; Yilei Li; Rakesh Ranjan; Björn Ommer (ECCV (21), 2024)

FMBoost: Boosting Latent Diffusion with Flow Matching. - Johannes Schusterbauer; Ming Gui; Pingchuan Ma 006; Nick Stracke; Stefan Andreas Baumann; Vincent Tao Hu; Björn Ommer (ECCV (61), 2024)

CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control and Altering of T2I Models. - Nick Stracke; Stefan Andreas Baumann; Joshua Susskind; Miguel Ángel Bautista 001; Björn Ommer (ECCV (88), 2024)

Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation. - Jiajun Wang; Morteza Ghahremani; Yitong Li; Björn Ommer; Christian Wachinger (NeurIPS, 2024)

Quantum Denoising Diffusion Models. - Michael Kölle 001; Gerhard Stenzel; Jonas Stein 001; Sebastian Zielinski; Björn Ommer; Claudia Linnhoff-Popien (QSW, 2024)

On the Challenges and Opportunities in Generative AI. - Laura Manduchi; Kushagra Pandey; Robert Bamler; Ryan Cotterell; Sina Däubener; Sophie Fellenz; Asja Fischer; Thomas Gärtner 004; Matthias Kirchler; Marius Kloft; Yingzhen Li; Christoph Lippert; et al. (CoRR, 2024)

DepthFM: Fast Monocular Depth Estimation with Flow Matching. - Ming Gui; Johannes S. Fischer; Ulrich Prestel; Pingchuan Ma 006; Dmytro Kotovenko; Olga Grebenkova; Stefan Andreas Baumann; Vincent Tao Hu; Björn Ommer (CoRR, 2024)

Enabling Visual Composition and Animation in Unsupervised Video Generation. - Aram Davtyan; Sepehr Sameni; Björn Ommer; Paolo Favaro (CoRR, 2024)

Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions. - Stefan Andreas Baumann; Felix Krause 002; Michael Neumayr; Nick Stracke; Vincent Tao Hu; Björn Ommer (CoRR, 2024)

CTRLorALTer: Conditional LoRAdapter for Efficient 0-Shot Control & Altering of T2I Models. - Nick Stracke; Stefan Andreas Baumann; Joshua M. Susskind; Miguel Ángel Bautista 001; Björn Ommer (CoRR, 2024)

Diffusion Models and Representation Learning: A Survey. - Michael Fuest; Pingchuan Ma 006; Ming Gui; Johannes S. Fischer; Vincent Tao Hu; Björn Ommer (CoRR, 2024)

Scaling Image Tokenizers with Grouped Spherical Quantization. - Jiangtao Wang; Zhen Qin; Yifan Zhang; Vincent Tao Hu; Björn Ommer; Rania Briq; Stefan Kesselheim (CoRR, 2024)

[MASK] is All You Need. - Vincent Tao Hu; Björn Ommer (CoRR, 2024)

State of the Art on Diffusion Models for Visual Computing. - Ryan Po; Wang Yifan 001; Vladislav Golyanik; Kfir Aberman; Jonathan T. Barron; Amit Bermano; Eric R. Chan; Tali Dekel; Aleksander Holynski; Angjoo Kanazawa; C. Karen Liu; Lingjie Liu; et al. (Comput. Graph. Forum, 2024)

Does VLM Classification Benefit from LLM Description Semantics? - Pingchuan Ma 006; Lennart Rietdorf; Dmytro Kotovenko; Vincent Tao Hu; Björn Ommer (AAAI, 2025)

CAGE: Unsupervised Visual Composition and Animation for Controllable Video Generation. - Aram Davtyan; Sepehr Sameni; Björn Ommer; Paolo Favaro (AAAI, 2025)

DepthFM: Fast Generative Monocular Depth Estimation with Flow Matching. - Ming Gui; Johannes Schusterbauer; Ulrich Prestel; Pingchuan Ma 006; Dmytro Kotovenko; Olga Grebenkova; Stefan Andreas Baumann; Vincent Tao Hu; Björn Ommer (AAAI, 2025)

Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions. - Stefan Andreas Baumann; Felix Krause 002; Michael Neumayr; Nick Stracke; Melvin Sevi; Vincent Tao Hu; Björn Ommer (CVPR, 2025)

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment. - Johannes Schusterbauer; Ming Gui; Frank Fundel; Björn Ommer (CVPR, 2025)

CleanDIFT: Diffusion Features without Noise. - Nick Stracke; Stefan Andreas Baumann; Kolja Bauer; Frank Fundel; Björn Ommer (CVPR, 2025)

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis. - Yousef Yeganeh; Azade Farshad; Ioannis Charisiadis; Marta Hasny; Martin Hartenberger; Björn Ommer; Nassir Navab; Ehsan Adeli 001 (CVPR, 2025)

Distillation of Diffusion Features for Semantic Correspondence. - Frank Fundel; Johannes Schusterbauer; Vincent Tao Hu; Björn Ommer (WACV, 2025)

On the Challenges and Opportunities in Generative AI. - Laura Manduchi; Clara Meister; Kushagra Pandey; Robert Bamler; Ryan Cotterell; Sina Däubener; Sophie Fellenz; Asja Fischer; Thomas Gärtner 004; Matthias Kirchler; Marius Kloft; Yingzhen Li; et al. (Trans. Mach. Learn. Res., 2025)

TREAD: Token Routing for Efficient Architecture-agnostic Diffusion Training. - Felix Krause 002; Timy Phan; Vincent Tao Hu; Björn Ommer (CoRR, 2025)

Unsupervised Behavior Analysis and Magnification using Deep Learning: Docker Image. - Biagio Brattoli; Uta Büchler; Michael Dorkenwald; Philipp Reiser; Linard Filli; Fritjof Helmchen; Anna-Sophia Wahl; Björn Ommer (Zenodo, 2025)

MaskFlow: Discrete Flows For Flexible and Efficient Long Video Generation. - Michael Fuest; Vincent Tao Hu; Björn Ommer (CoRR, 2025)

EDGS: Eliminating Densification for Efficient Convergence of 3DGS. - Dmytro Kotovenko; Olga Grebenkova; Björn Ommer (CoRR, 2025)

Can Prompt Difficulty be Online Predicted for Accelerating RL Finetuning of Reasoning Models? - Yun Qu 002; Qi Wang; Yixiu Mao; Vincent Tao Hu; Björn Ommer; Xiangyang Ji (CoRR, 2025)

SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models. - Pingchuan Ma 006; Xiaopei Yang; Yusong Li; Ming Gui; Felix Krause 002; Johannes Schusterbauer; Björn Ommer (CoRR, 2025)