Text-to-3D Generation - Groups

X-Dreamer Dataset

The dataset used in the paper for text-to-3D content creation, which consists of 3D assets generated from text prompts.

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Classifier Score Distillation

Text-to-3D generation has made remarkable progress recently, particularly with methods based on Score Distillation Sampling (SDS) that leverages pre-trained 2D diffusion models.

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C3DAG: Controlled 3D Animal Generation using 3D pose guidance

A novel pose-Controlled text-to-3D Animal Generation framework which generates a high quality 3D animal consistent with a given pose.

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Debiased Score Distillation Sampling

Debiased Score Distillation Sampling (D-SDS) is a method for improving the realism and alleviating the Janus problem of generated 3D objects.

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CompoNeRF

CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layout

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HIFA: HIGH-FIDELITY TEXT-TO-3D GENERATION

The dataset used in the paper for text-to-3D generation, generated using pre-trained text-to-image diffusion models.

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Text2Shape

Text2Shape is a dataset of 8,447 table instances and 6,591 chair instances from the ShapeNet dataset, along with 75,344 natural language descriptions.

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GradeADreamer: Enhanced Text-to-3D Generation

Text-to-3D generation has shown promising results, yet common challenges such as the Multi-face Janus problem and extended generation time for high-quality assets. In this...

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T3Bench

The dataset used in the Sculpt3D paper, containing 100 text prompts for 3D object generation.

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Magic3D

Magic3D: High-resolution text-to-3D content creation.

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Prolific-Dreamer

Prolific-Dreamer: High-fidelity and diverse text-to-3D generation with variational score distillation.

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ET3D dataset

The dataset used in the paper for text-to-3D generation, consisting of 5,000 different prompts and 800,000 generated images.

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HeadSculpt Testing Dataset

The dataset used in the paper for testing the HeadSculpt model, which consists of 3D head avatars generated from textual prompts.

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HeadSculpt Dataset

The dataset used in the paper for training and testing the HeadSculpt model, which consists of 3D head avatars generated from textual prompts.

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LucidDreamer

The dataset used in the paper is a text-to-3D generation framework, named the LucidDreamer, to distill high-fidelity textures and shapes from pretrained 2D diffusion models.

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Points-to-3D: Bridging the Gap between Sparse Points and Shape-Controllable T...

Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on...

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VP3D: Unleashing 2D Visual Prompt for Text-to-3D Generation

Text-to-3D generation using 2D visual prompts

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SteinDreamer

The dataset used in the paper SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity

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Retrieval-Augmented Score Distillation for Text-to-3D Generation

Text-to-3D generation has emerged as an important application that enables non-experts to easily create 3D contents. The conventional approaches for text-to-3D train a...

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CG3D: Compositional Generation for Text-to-3D via Gaussian Splatting

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24 datasets found