paper-with-me

홈 › Papers

Make-It-Vivid: Dressing Your Animatable Biped Cartoon Characters from Text

2024-03-25 · CVPR 2024 1 · Junshu Tang, Yanhong Zeng, Ke Fan, Xuheng Wang, Bo Dai, Kai Chen, Lizhuang Ma

Creating and animating 3D biped cartoon characters is crucial and valuable in various applications. Compared with geometry, the diverse texture design plays an important role in making 3D biped cartoon characters vivid and charming. Therefore, we focus on automatic texture design for cartoon characters based on input instructions. This is challenging for domain-specific requirements and a lack of high-quality data. To address this challenge, we propose Make-It-Vivid, the first attempt to enable high-quality texture generation from text in UV space. We prepare a detailed text-texture paired data for 3D characters by using vision-question-answering agents. Then we customize a pretrained text-to-image model to generate texture map with template structure while preserving the natural 2D image knowledge. Furthermore, to enhance fine-grained details, we propose a novel adversarial learning scheme to shorten the domain gap between original dataset and realistic texture domain. Extensive experiments show that our approach outperforms current texture generation methods, resulting in efficient character texturing and faithful generation with prompts. Besides, we showcase various applications such as out of domain generation and texture stylization. We also provide an efficient generation system for automatic text-guided textured character generation and animation.

📄 PDF Abstract BibTeX arXiv:2403.16897

Code (0)

등록된 구현이 없습니다.

Tasks

Question AnsweringTexture Synthesis

Methods 이 논문이 사용한 방법론

Focus 설명 없음

Similar Papers 제목 키워드 기반

DreamWaltz: Make a Scene with Complex 3D Animatable Avatars

2023-05-21 · NeurIPS 2023 11

We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encouraging results for text-to-3D generation …

3D GenerationText to 3D

Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance

2023-06-01 · Jinbo Xing, Menghan Xia, Yuxin Liu, Yuechen Zhang 외

Creating a vivid video from the event or scenario in our imagination is a truly fascinating experience. Recent advancements in text-to-video synthesis have unveiled the potential to achieve this with prompts only. While …

Image GenerationVideo Generation

Constrained Reinforcement Learning for Unstable Point-Feet Bipedal Locomotion Applied to the Bolt Robot

2025-08-04 · Constant Roux, Elliot Chane-Sane, Ludovic De Matteïs, Thomas Flayols 외 arxiv

Bipedal locomotion is a key challenge in robotics, particularly for robots like Bolt, which have a point-foot design. This study explores the control of such underactuated robots using constrained reinforcement learning,…

Reinforcement Learning

Make-It-Animatable: An Efficient Framework for Authoring Animation-Ready 3D Characters

2024-11-27 · CVPR 2025 1 · Zhiyang Guo, Jinxu Xiang, Kai Ma, Wengang Zhou 외

3D characters are essential to modern creative industries, but making them animatable often demands extensive manual work in tasks like rigging and skinning. Existing automatic rigging tools face several limitations, inc…

VividVoice: A Unified Framework for Scene-Aware Visually-Driven Speech Synthesis

2026-02-01 · Chengyuan Ma, Jiawei Jin, Ruijie Xiong, Chunxiang Jin 외 arxiv

We introduce and define a novel task-Scene-Aware Visually-Driven Speech Synthesis, aimed at addressing the limitations of existing speech generation models in creating immersive auditory experiences that align with the r…

Speech Synthesis