activity
20232026
most citedMeta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials

3 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

ActionMesh: Animated 3D Mesh Generation with Temporal 3D Diffusion

Remy Sabathier, David Novotny, Niloy J. Mitra +1

Generating animated 3D objects is at the heart of many applications, yet most advanced works are typically difficult to apply in practice because of their limited setup, their long…

cs.CV2025

WildCAT3D: Appearance-Aware Multi-View Diffusion in the Wild

Morris Alper, David Novotny, Filippos Kokkinos +2

Despite recent advances in sparse novel view synthesis (NVS) applied to object-centric scenes, scene-level NVS remains a challenge. A central issue is the lack of available clean m…

cs.CV2025

LIM: Large Interpolator Model for Dynamic Reconstruction

Remy Sabathier, Niloy J. Mitra, David Novotny

Reconstructing dynamic assets from video data is central to many in computer vision and graphics tasks. Existing 4D reconstruction approaches are limited by category-specific model…

cs.CV2025

Twinner: Shining Light on Digital Twins in a Few Snaps

Jesus Zarzar, Tom Monnier, Roman Shapovalov +2

We present the first large reconstruction model, Twinner, capable of recovering a scene's illumination as well as an object's geometry and material properties from only a few posed…

cs.CV2024★ 3 cited

Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials

Yawar Siddiqui, Tom Monnier, Filippos Kokkinos +8

We present Meta 3D AssetGen (AssetGen), a significant advancement in text-to-3D generation which produces faithful, high-quality meshes with texture and material control. Compared…

cs.CV2024

Animal Avatars: Reconstructing Animatable 3D Animals from Casual Videos

Remy Sabathier, Niloy J. Mitra, David Novotny

We present a method to build animatable dog avatars from monocular videos. This is challenging as animals display a range of (unpredictable) non-rigid movements and have a variety…

cs.CV2023

GOEmbed: Gradient Origin Embeddings for Representation Agnostic 3D Feature Learning

Animesh Karnewar, Roman Shapovalov, Tom Monnier +3

Encoding information from 2D views of an object into a 3D representation is crucial for generalized 3D feature extraction. Such features can then enable 3D reconstruction, 3D gener…