Textoon: Generating Vivid 2D Cartoon Characters from Text Descriptions
- URL: http://arxiv.org/abs/2501.10020v2
- Date: Tue, 04 Feb 2025 13:28:14 GMT
- Title: Textoon: Generating Vivid 2D Cartoon Characters from Text Descriptions
- Authors: Chao He, Jianqiang Ren, Yuan Dong, Jianjing Xiang, Xiejie Shen, Weihao Yuan, Liefeng Bo,
- Abstract summary: We introduce Textoon, an innovative method for generating diverse 2D cartoon characters in the Live2D format based on text descriptions.<n>The Textoon leverages cutting-edge language and vision models to comprehend textual intentions and generate 2D appearance.
- Score: 12.699709535247678
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The 2D cartoon style is a prominent art form in digital character creation, particularly popular among younger audiences. While advancements in digital human technology have spurred extensive research into photorealistic digital humans and 3D characters, interactive 2D cartoon characters have received comparatively less attention. Unlike 3D counterparts, which require sophisticated construction and resource-intensive rendering, Live2D, a widely-used format for 2D cartoon characters, offers a more efficient alternative, which allows to animate 2D characters in a manner that simulates 3D movement without the necessity of building a complete 3D model. Furthermore, Live2D employs lightweight HTML5 (H5) rendering, improving both accessibility and efficiency. In this technical report, we introduce Textoon, an innovative method for generating diverse 2D cartoon characters in the Live2D format based on text descriptions. The Textoon leverages cutting-edge language and vision models to comprehend textual intentions and generate 2D appearance, capable of creating a wide variety of stunning and interactive 2D characters within one minute. The project homepage is https://human3daigc.github.io/Textoon_webpage/.
Related papers
- CartoonAlive: Towards Expressive Live2D Modeling from Single Portraits [1.3695921386586667]
We present CartoonAlive, an innovative method for generating high-quality Live2D digital humans from a single input portrait image.<n>Our work provides a practical and scalable solution for creating interactive 2D cartoon characters, opening new possibilities in digital content creation and virtual character animation.
arXiv Detail & Related papers (2025-07-23T08:52:48Z) - VP3D: Unleashing 2D Visual Prompt for Text-to-3D Generation [96.62867261689037]
We introduce a novel Visual Prompt-guided text-to-3D diffusion model (VP3D)
VP3D explicitly unleashes the visual appearance knowledge in 2D visual prompt to boost text-to-3D generation.
Our experiments show that the 2D Visual Prompt in our VP3D significantly eases the learning of visual appearance of 3D models.
arXiv Detail & Related papers (2024-03-25T17:59:31Z) - Make-It-Vivid: Dressing Your Animatable Biped Cartoon Characters from Text [38.591390310534024]
We focus on automatic texture design for cartoon characters on input instructions.
This is challenging for domain-specific requirements and a lack of high-quality data.
We propose Make-ItVivi the first attempt to enable high-quality texture generation from text in UV.
arXiv Detail & Related papers (2024-03-25T16:08:04Z) - Make-A-Character: High Quality Text-to-3D Character Generation within
Minutes [28.30067870250642]
We propose a user-friendly framework named Make-A-Character (Mach) to create lifelike 3D avatars from text descriptions.
Our system offers an intuitive approach for users to craft controllable, realistic, fully-realized 3D characters that meet their expectations within 2 minutes.
arXiv Detail & Related papers (2023-12-24T08:11:39Z) - Control3D: Towards Controllable Text-to-3D Generation [107.81136630589263]
We present a text-to-3D generation conditioning on the additional hand-drawn sketch, namely Control3D.
A 2D conditioned diffusion model (ControlNet) is remoulded to guide the learning of 3D scene parameterized as NeRF.
We exploit a pre-trained differentiable photo-to-sketch model to directly estimate the sketch of the rendered image over synthetic 3D scene.
arXiv Detail & Related papers (2023-11-09T15:50:32Z) - TADA! Text to Animatable Digital Avatars [57.52707683788961]
TADA takes textual descriptions and produces expressive 3D avatars with high-quality geometry and lifelike textures.
We derive an optimizable high-resolution body model from SMPL-X with 3D displacements and a texture map.
We render normals and RGB images of the generated character and exploit their latent embeddings in the SDS training process.
arXiv Detail & Related papers (2023-08-21T17:59:10Z) - DreamHuman: Animatable 3D Avatars from Text [41.30635787166307]
We present DreamHuman, a method to generate realistic animatable 3D human avatar models solely from textual descriptions.
Our 3D models have diverse appearance, clothing, skin tones and body shapes, and significantly outperform both generic text-to-3D approaches and previous text-based 3D avatar generators in visual fidelity.
arXiv Detail & Related papers (2023-06-15T17:58:21Z) - Text-guided 3D Human Generation from 2D Collections [69.04031635550294]
We introduce Text-guided 3D Human Generation (texttT3H), where a model is to generate a 3D human, guided by the fashion description.
CCH adopts cross-modal attention to fuse compositional human rendering with the extracted fashion semantics.
We conduct evaluations on DeepFashion and SHHQ with diverse fashion attributes covering the shape, fabric, and color of upper and lower clothing.
arXiv Detail & Related papers (2023-05-23T17:50:15Z) - AG3D: Learning to Generate 3D Avatars from 2D Image Collections [96.28021214088746]
We propose a new adversarial generative model of realistic 3D people from 2D images.
Our method captures shape and deformation of the body and loose clothing by adopting a holistic 3D generator.
We experimentally find that our method outperforms previous 3D- and articulation-aware methods in terms of geometry and appearance.
arXiv Detail & Related papers (2023-05-03T17:56:24Z) - HyperStyle3D: Text-Guided 3D Portrait Stylization via Hypernetworks [101.36230756743106]
This paper is inspired by the success of 3D-aware GANs that bridge 2D and 3D domains with 3D fields as the intermediate representation for rendering 2D images.
We propose a novel method, dubbed HyperStyle3D, based on 3D-aware GANs for 3D portrait stylization.
arXiv Detail & Related papers (2023-04-19T07:22:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.