activity
20232026
most citedMeta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects

3 citations · 7 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CV2026

Go-with-the-Track: Video Compositing and Motion Control with Point Tracking

Koichi Namekata, Yash Kant, Zhizheng Liu +9

Filmmaking demands precise motion control and reference image compositing -- capabilities that existing methods treat separately. Point-track-conditioned image-to-video models rest…

cs.CV2026

MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer

Weiyu Li, Antoine Toisoul, Tom Monnier +4

We present MeshFlow, a new method for generating artist-like 3D meshes. Current mesh generators often adopt Auto-Regressive (AR) next-token prediction, a natural choice given the d…

cs.GR2026

AssetGen: Deployable 3D Asset Generation at Interactive Speed

Dilin Wang, Xiaoyu Xiang, Kihyuk Sohn +14

While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployability as afterthoughts. We presen…

cs.CV2026

MeshReGen: A Unified 3D Geometry Regeneration Framework

Geon Yeong Park, Roman Shapovalov, Rakesh Ranjan +3

We consider the problem of regenerating 3D objects from 2D images and initial 3D shapes. Most 3D generators operate in a one-shot fashion, converting text or images to a 3D object…

cs.CV2026

Free-Range Gaussians: Non-Grid-Aligned Generative 3D Gaussian Reconstruction

Ahan Shabanov, Peter Hedman, Ethan Weber +10

We present Free-Range Gaussians, a multi-view reconstruction method that predicts non-pixel, non-voxel-aligned 3D Gaussians from as few as four images. This is done through flow ma…

cs.CV2025

WorldGen: From Text to Traversable and Interactive 3D Worlds

Dilin Wang, Hyunyoung Jung, Tom Monnier +22

We introduce WorldGen, a system that enables the automatic creation of large-scale, interactive 3D worlds directly from text prompts. Our approach transforms natural language descr…

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.CV2025

UnCommon Objects in 3D

Xingchen Liu, Piyush Tayal, Jianyuan Wang +10

We introduce Uncommon Objects in 3D (uCO3D), a new object-centric dataset for 3D deep learning and 3D generative AI. uCO3D is the largest publicly-available collection of high-reso…

cs.CV2024

CatFree3D: Category-agnostic 3D Object Detection with Diffusion

Wenjing Bian, Zirui Wang, Andrea Vedaldi

Image-based 3D object detection is widely employed in applications such as autonomous vehicles and robotics, yet current systems struggle with generalisation due to complex problem…

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★ 3 cited

Meta 3D TextureGen: Fast and Consistent Texture Generation for 3D Objects

Raphael Bensadoun, Yanir Kleiman, Idan Azuri +4

The recent availability and adaptability of text-to-image models has sparked a new era in many related domains that benefit from the learned text priors as well as high-quality and…

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…

cs.CV2023★ 1 cited

Free3D: Consistent Novel View Synthesis without 3D Representation

Chuanxia Zheng, Andrea Vedaldi

We introduce Free3D, a simple accurate method for monocular open-set novel view synthesis (NVS). Similar to Zero-1-to-3, we start from a pre-trained 2D image generator for generali…

cs.CV2023

Instant Uncertainty Calibration of NeRFs Using a Meta-Calibrator

Niki Amini-Naieni, Tomas Jakab, Andrea Vedaldi +1

Although Neural Radiance Fields (NeRFs) have markedly improved novel view synthesis, accurate uncertainty quantification in their image predictions remains an open problem. The pre…