9 citations · 12 across the 14 of their papers we have counts for
14 papers
EditVerse3D: High-Quality 3D Object Editing with Region-Aware Learning
Youtan Yin, Yanning Zhou, Jiacheng Wei +6
Local editing of 3D objects remains a long-standing challenge. When interacting with 3D content, humans naturally tend to specify a coarse region of interest for modification rathe…
Hunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material
Team Hunyuan3D, Shuhui Yang, Mingxin Yang +50
3D AI-generated content (AIGC) is a passionate field that has significantly accelerated the creation of 3D models in gaming, film, and design. Despite the development of several gr…
ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang +6
Human mesh recovery (HMR) from a single image is inherently ill-posed due to depth ambiguity and occlusions. Probabilistic methods have tried to solve this by generating numerous p…
CADCrafter: Generating Computer-Aided Design Models from Unconstrained Images
Cheng Chen, Jiacheng Wei, Tianrun Chen +8
Creating CAD digital twins from the physical world is crucial for manufacturing, design, and simulation. However, current methods typically rely on costly 3D scanning with labor-in…
IPVTON: Image-based 3D Virtual Try-on with Image Prompt Adapter
Xiaojing Zhong, Zhonghua Wu, Xiaofeng Yang +2
Given a pair of images depicting a person and a garment separately, image-based 3D virtual try-on methods aim to reconstruct a 3D human model that realistically portrays the person…
Towards Lifelong Few-Shot Customization of Text-to-Image Diffusion
Nan Song, Xiaofeng Yang, Ze Yang +1
Lifelong few-shot customization for text-to-image diffusion aims to continually generalize existing models for new tasks with minimal data while preserving old knowledge. Current c…
InteractPro: A Unified Framework for Motion-Aware Image Composition
Weijing Tao, Xiaofeng Yang, Miaomiao Cui +1
We introduce InteractPro, a comprehensive framework for dynamic motion-aware image composition. At its core is InteractPlan, an intelligent planner that leverages a Large Vision La…
DeCo: Decoupled Human-Centered Diffusion Video Editing with Motion Consistency
Xiaojing Zhong, Xinyi Huang, Xiaofeng Yang +2
Diffusion models usher a new era of video editing, flexibly manipulating the video contents with text prompts. Despite the widespread application demand in editing human-centered v…
Text-to-Image Rectified Flow as Plug-and-Play Priors
Xiaofeng Yang, Cheng Chen, Xulei Yang +2
Large-scale diffusion models have achieved remarkable performance in generative tasks. Beyond their initial training applications, these models have proven their ability to functio…
Sync4D: Video Guided Controllable Dynamics for Physics-Based 4D Generation
Zhoujie Fu, Jiacheng Wei, Wenhao Shen +5
In this work, we introduce a novel approach for creating controllable dynamics in 3D-generated Gaussians using casually captured reference videos. Our method transfers the motion o…
Magic-Boost: Boost 3D Generation with Multi-View Conditioned Diffusion
Fan Yang, Jianfeng Zhang, Yichun Shi +7
Benefiting from the rapid development of 2D diffusion models, 3D content generation has witnessed significant progress. One promising solution is to finetune the pre-trained 2D dif…
Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior
Cheng Chen, Xiaofeng Yang, Fan Yang +5
Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the bac…
GaussianEditor: Swift and Controllable 3D Editing with Gaussian Splatting
Yiwen Chen, Zilong Chen, Chi Zhang +7
3D editing plays a crucial role in many areas such as gaming and virtual reality. Traditional 3D editing methods, which rely on representations like meshes and point clouds, often…
Learn to Optimize Denoising Scores for 3D Generation: A Unified and Improved Diffusion Prior on NeRF and 3D Gaussian Splatting
Xiaofeng Yang, Yiwen Chen, Cheng Chen +5
We propose a unified framework aimed at enhancing the diffusion priors for 3D generation tasks. Despite the critical importance of these tasks, existing methodologies often struggl…