Search Results for author: Joseph Lambourne

Found 5 papers, 1 papers with code

Detecting Generative Parroting through Overfitting Masked Autoencoders

no code implementations27 Mar 2024 Saeid Asgari Taghanaki, Joseph Lambourne

The advent of generative AI models has revolutionized digital content creation, yet it introduces challenges in maintaining copyright integrity due to generative parroting, where models mimic their training data too closely.

Sketch-A-Shape: Zero-Shot Sketch-to-3D Shape Generation

no code implementations8 Jul 2023 Aditya Sanghi, Pradeep Kumar Jayaraman, Arianna Rampini, Joseph Lambourne, Hooman Shayani, Evan Atherton, Saeid Asgari Taghanaki

Significant progress has recently been made in creative applications of large pre-trained models for downstream tasks in 3D vision, such as text-to-shape generation.

3D Shape Generation Text-to-Shape Generation

UVStyle-Net: Unsupervised Few-shot Learning of 3D Style Similarity Measure for B-Reps

1 code implementation ICCV 2021 Peter Meltzer, Hooman Shayani, Amir Khasahmadi, Pradeep Kumar Jayaraman, Aditya Sanghi, Joseph Lambourne

Boundary Representations (B-Reps) are the industry standard in 3D Computer Aided Design/Manufacturing (CAD/CAM) and industrial design due to their fidelity in representing stylistic details.

Computational Efficiency Unsupervised Few-Shot Learning

Fusion 360 Gallery: A Dataset and Environment for Programmatic CAD Reconstruction

no code implementations28 Sep 2020 Karl Willis, Yewen Pu, Jieliang Luo, Hang Chu, Tao Du, Joseph Lambourne, Armando Solar-Lezama, Wojciech Matusik

We provide a dataset of 8, 625 designs, comprising sequential sketch and extrude modeling operations, together with a complementary environment called the Fusion 360 Gym, to assist with performing CAD reconstruction.

CAD Reconstruction

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