Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition. - Frederik Warburg; Søren Hauberg; Manuel López-Antequera; Pau Gargallo; Yubin Kuang; Javier Civera 001 (CVPR, 2020)

Probabilistic Spatial Transformers for Bayesian Data Augmentation. - Pola Schwöbel; Frederik Warburg; Martin Jørgensen; Kristoffer H. Madsen; Søren Hauberg (CoRR, 2020)

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. - Frederik Warburg; Martin Jørgensen; Javier Civera 001; Søren Hauberg (ICCV, 2021)

Laplacian Autoencoders for Learning Stochastic Representations. - Marco Miani; Frederik Warburg; Pablo Moreno-Muñoz; Nicki Skafte Detlefsen; Søren Hauberg (NeurIPS, 2022)

Probabilistic spatial transformer networks. - Pola Schwöbel; Frederik Rahbæk Warburg; Martin Jørgensen; Kristoffer Hougaard Madsen; Søren Hauberg (UAI, 2022)

SparseFormer: Attention-based Depth Completion Network. - Frederik Warburg; Michaël Ramamonjisoa; Manuel López-Antequera (CoRR, 2022)

Searching for Structure in Unfalsifiable Claims. - Peter Ebert Christensen; Frederik Warburg; Menglin Jia; Serge J. Belongie (CoRR, 2022)

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization. - Andrea Vallone; Frederik Warburg; Hans Hansen; Søren Hauberg; Javier Civera 001 (IEEE Robotics Autom. Lett., 2022)

Self-Supervised Depth Completion for Active Stereo. - Frederik Warburg; Daniel Hernández Juárez; Juan Tarrio; Alexander Vakhitov; Ujwal Bonde; Pablo F. Alcantarilla (IEEE Robotics Autom. Lett., 2022)

K-Planes: Explicit Radiance Fields in Space, Time, and Appearance. - Sara Fridovich-Keil; Giacomo Meanti; Frederik Rahbæk Warburg; Benjamin Recht; Angjoo Kanazawa (CVPR, 2023)

Nerfbusters: Removing Ghostly Artifacts from Casually Captured NeRFs. - Frederik Warburg; Ethan Weber; Matthew Tancik; Aleksander Holynski; Angjoo Kanazawa (ICCV, 2023)

Learning to Taste: A Multimodal Wine Dataset. - Thoranna Bender; Simon Møe Sørensen; Alireza Kashani; Kristjan Eldjarn Hjorleifsson; Grethe Hyldig; Søren Hauberg; Serge J. Belongie; Frederik Warburg (NeurIPS, 2023)

Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval. - Frederik Warburg; Marco Miani; Silas Brack; Søren Hauberg (NeurIPS, 2023)

Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty. - Kilian Zepf; Selma Wanna; Marco Miani; Juston Moore; Jes Frellsen; Søren Hauberg; Aasa Feragen; Frederik Warburg (CoRR, 2023)

DAC: Detector-Agnostic Spatial Covariances for Deep Local Features. - Javier Tirado-Garín; Frederik Warburg; Javier Civera 001 (3DV, 2024)

Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification. - Kilian Zepf; Selma Wanna; Marco Miani; Juston Moore; Jes Frellsen; Søren Hauberg; Frederik Warburg; Aasa Feragen (MICCAI (8), 2024)

Volumetric Disentanglement for 3D Scene Manipulation. - Sagie Benaim; Frederik Warburg; Peter Ebert Christensen; Serge J. Belongie (WACV, 2024)

Toon3D: Seeing Cartoons from a New Perspective. - Ethan Weber; Riley Peterlinz; Rohan Mathur; Frederik Warburg; Alexei A. Efros; Angjoo Kanazawa (CoRR, 2024)