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Papers Text-to-Shape Generation

“Text-to-Shape Generation” 태그가 달린 논문 8편 · 필터 해제

Cube: A Roblox View of 3D Intelligence

2025-03-19 · Foundation AI Team, Kiran Bhat, Nishchaie Khanna, Karun Channa 외

Foundation models trained on vast amounts of data have demonstrated remarkable reasoning and generation capabilities in the domains of text, images, audio and video. Our goal at Roblox is to build such a foundation model…

Scene GenerationText GenerationText-to-Shape Generation

HyperSDFusion: Bridging Hierarchical Structures in Language and Geometry for Enhanced 3D Text2Shape Generation

2024-03-01 · CVPR 2024 1 · Zhiying Leng, Tolga Birdal, Xiaohui Liang, Federico Tombari

3D shape generation from text is a fundamental task in 3D representation learning. The text-shape pairs exhibit a hierarchical structure, where a general text like ``chair" covers all 3D shapes of the chair, while more d…

3D Shape GenerationRepresentation LearningText-to-Shape Generation

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

2023-07-08 · Aditya Sanghi, Pradeep Kumar Jayaraman, Arianna Rampini, Joseph Lambourne 외

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. This motivates our investigation of how these pre-trai…

3D Shape GenerationText-to-Shape Generation

ZeroForge: Feedforward Text-to-Shape Without 3D Supervision

2023-06-14 · Kelly O. Marshall, Minh Pham, Ameya Joshi, Anushrut Jignasu 외

Current state-of-the-art methods for text-to-shape generation either require supervised training using a labeled dataset of pre-defined 3D shapes, or perform expensive inference-time optimization of implicit neural repre…

Text-to-Shape Generation

Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Models

2022-12-28 · CVPR 2023 1 · Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao 외

Recent CLIP-guided 3D optimization methods, such as DreamFields and PureCLIPNeRF, have achieved impressive results in zero-shot text-to-3D synthesis. However, due to scratch training and random initialization without pri…

Image GenerationText to 3DText-to-Shape Generation

SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation

2022-12-08 · CVPR 2023 1 · Yen-Chi Cheng, Hsin-Ying Lee, Sergey Tulyakov, Alexander Schwing 외

In this work, we present a novel framework built to simplify 3D asset generation for amateur users. To enable interactive generation, our method supports a variety of input modalities that can be easily provided by a hum…

3D Reconstruction3D Shape GenerationDecoderText to 3D+1

CLIP-Sculptor: Zero-Shot Generation of High-Fidelity and Diverse Shapes from Natural Language

2022-11-02 · CVPR 2023 1 · Aditya Sanghi, Rao Fu, Vivian Liu, Karl Willis 외

Recent works have demonstrated that natural language can be used to generate and edit 3D shapes. However, these methods generate shapes with limited fidelity and diversity. We introduce CLIP-Sculptor, a method to address…

DiversityImage GenerationText to 3DText-to-Shape Generation

CLIP-Forge: Towards Zero-Shot Text-to-Shape Generation

2021-10-06 · CVPR 2022 1 · Aditya Sanghi, Hang Chu, Joseph G. Lambourne, Ye Wang 외

Generating shapes using natural language can enable new ways of imagining and creating the things around us. While significant recent progress has been made in text-to-image generation, text-to-shape generation remains a…

Image GenerationText to Image GenerationText-to-Image GenerationText-to-Shape Generation+1
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