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20222024
most citedCNOS: A Strong Baseline for CAD-based Novel Object Segmentation

4 citations · 5 across the 9 of their papers we have counts for

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cs.CV2024

Instant3dit: Multiview Inpainting for Fast Editing of 3D Objects

Amir Barda, Matheus Gadelha, Vladimir G. Kim +3

We propose a generative technique to edit 3D shapes, represented as meshes, NeRFs, or Gaussian Splats, in approximately 3 seconds, without the need for running an SDS type of optim…

cs.CV2024

TutteNet: Injective 3D Deformations by Composition of 2D Mesh Deformations

Bo Sun, Thibault Groueix, Chen Song +2

This work proposes a novel representation of injective deformations of 3D space, which overcomes existing limitations of injective methods: inaccuracy, lack of robustness, and inco…

cs.CV2024

MatAtlas: Text-driven Consistent Geometry Texturing and Material Assignment

Duygu Ceylan, Valentin Deschaintre, Thibault Groueix +5

We present MatAtlas, a method for consistent text-guided 3D model texturing. Following recent progress we leverage a large scale text-to-image generation model (e.g., Stable Diffus…

cs.CV2024

Learning Continuous 3D Words for Text-to-Image Generation

Ta-Ying Cheng, Matheus Gadelha, Thibault Groueix +4

Current controls over diffusion models (e.g., through text or ControlNet) for image generation fall short in recognizing abstract, continuous attributes like illumination direction…

cs.CV2023

3DMiner: Discovering Shapes from Large-Scale Unannotated Image Datasets

Ta-Ying Cheng, Matheus Gadelha, Soren Pirk +4

We present 3DMiner -- a pipeline for mining 3D shapes from challenging large-scale unannotated image datasets. Unlike other unsupervised 3D reconstruction methods, we assume that,…

cs.CV20234 cited

CNOS: A Strong Baseline for CAD-based Novel Object Segmentation

Van Nguyen Nguyen, Thibault Groueix, Georgy Ponimatkin +2

We propose a simple three-stage approach to segment unseen objects in RGB images using their CAD models. Leveraging recent powerful foundation models, DINOv2 and Segment Anything,…