docExtractor: An off-the-shelf historical document element extraction. - Tom Monnier; Mathieu Aubry (ICFHR, 2020)

Deep Transformation-Invariant Clustering. - Tom Monnier; Thibault Groueix; Mathieu Aubry (NeurIPS, 2020)

A Web Application for Watermark Recognition. - Oumayma Bounou; Tom Monnier; Ilaria Pastrolin; Xi Shen 001; Christine Benevent; Marie-Françoise Limon-Bonnet; François Bougard; Mathieu Aubry; Marc H. Smith; Olivier Poncet; Pierre-Guillaume Raverdy (J. Data Min. Digit. Humanit., 2020)

Representing Shape Collections With Alignment-Aware Linear Models. - Romain Loiseau; Tom Monnier; Mathieu Aubry; Loïc Landrieu (3DV, 2021)

Unsupervised Layered Image Decomposition into Object Prototypes. - Tom Monnier; Elliot Vincent; Jean Ponce; Mathieu Aubry (ICCV, 2021)

Share with Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency. - Tom Monnier; Matthew Fisher; Alexei A. Efros; Mathieu Aubry (ECCV (1), 2022)

Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason? - Monika Wysoczanska; Tom Monnier; Tomasz Trzcinski; David Picard (CoRR, 2022)

Spatially-Consistent Feature Matching and Learning for Heritage Image Analysis. - Xi Shen 001; Robin Champenois; Shiry Ginosar; Ilaria Pastrolin; Morgane Rousselot; Oumayma Bounou; Tom Monnier; Spyros Gidaris; François Bougard; Pierre-Guillaume Raverdy; Marie-Françoise Limon-Bonnet; Christine Benevent; et al. (Int. J. Comput. Vis., 2022)

MACARONS: Mapping and Coverage Anticipation with RGB Online Self-Supervision. - Antoine Guédon; Tom Monnier; Pascal Monasse; Vincent Lepetit (CVPR, 2023)

Differentiable Blocks World: Qualitative 3D Decomposition by Rendering Primitives. - Tom Monnier; Jake Austin; Angjoo Kanazawa; Alexei A. Efros; Mathieu Aubry (NeurIPS, 2023)

The Learnable Typewriter: A Generative Approach to Text Line Analysis. - Ioannis Siglidis; Nicolas Gonthier; Julien Gaubil; Tom Monnier; Mathieu Aubry (CoRR, 2023)

Unsupervised Image Analysis by Synthesis. (Analyse d'image non supervisée par synthèse). - Tom Monnier (2023)

GOEmbed: Gradient Origin Embeddings for Representation Agnostic 3D Feature Learning. - Animesh Karnewar; Roman Shapovalov; Tom Monnier; Andrea Vedaldi; Niloy J. Mitra; David Novotný (ECCV (88), 2024)

The Learnable Typewriter: A Generative Approach to Text Analysis. - Ioannis Siglidis; Nicolas Gonthier; Julien Gaubil; Tom Monnier; Mathieu Aubry (ICDAR (2), 2024)

Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials. - Yawar Siddiqui; Tom Monnier; Filippos Kokkinos; Mahendra Kariya; Yanir Kleiman; Emilien Garreau; Oran Gafni; Natalia Neverova; Andrea Vedaldi; Roman Shapovalov; David Novotný (NeurIPS, 2024)

Toward Unsupervised Visual Reasoning: Do Off-the-Shelf Features Know How to Reason? - Monika Wysoczanska; Tom Monnier; Tomasz Trzcinski; David Picard (IEEE Access, 2024)

Meta 3D Gen. - Raphael Bensadoun; Tom Monnier; Yanir Kleiman; Filippos Kokkinos; Yawar Siddiqui; Mahendra Kariya; Omri Harosh; Roman Shapovalov; Benjamin Graham; Emilien Garreau; Animesh Karnewar; Ang Cao; et al. (CoRR, 2024)

PartGen: Part-level 3D Generation and Reconstruction with Multi-view Diffusion Models. - Minghao Chen; Roman Shapovalov; Iro Laina; Tom Monnier; Jianyuan Wang; David Novotný; Andrea Vedaldi (CVPR, 2025)

UnCommon Objects in 3D. - Xingchen Liu; Piyush Tayal; Jianyuan Wang; Jesus Zarzar; Tom Monnier; Konstantinos Tertikas; Jiali Duan; Antoine Toisoul; Jason Y. Zhang 001; Natalia Neverova; Andrea Vedaldi; Roman Shapovalov; et al. (CVPR, 2025)

Twinner: Shining Light on Digital Twins in a Few Snaps. - Jesus Zarzar; Tom Monnier; Roman Shapovalov; Andrea Vedaldi; David Novotný (CVPR, 2025)

WildCAT3D: Appearance-Aware Multi-View Diffusion in the Wild. - Morris Alper; David Novotný; Filippos Kokkinos; Hadar Averbuch-Elor; Tom Monnier (CoRR, 2025)

AutoPartGen: Autogressive 3D Part Generation and Discovery. - Minghao Chen; Jianyuan Wang; Roman Shapovalov; Tom Monnier; Hyunyoung Jung; Dilin Wang; Rakesh Ranjan; Iro Laina; Andrea Vedaldi (CoRR, 2025)