most citedHunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

9 citations · 9 across the 11 of their papers we have counts for

collaborators

12 papers

cs.CV2025

Wan-Move: Motion-controllable Video Generation via Latent Trajectory Guidance

Ruihang Chu, Yefei He, Zhekai Chen +10

We present Wan-Move, a simple and scalable framework that brings motion control to video generative models. Existing motion-controllable methods typically suffer from coarse contro…

cs.CV2025

Explainable Melanoma Diagnosis with Contrastive Learning and LLM-based Report Generation

Junwen Zheng, Xinran Xu, Li Rong Wang +5

Deep learning has demonstrated expert-level performance in melanoma classification, positioning it as a powerful tool in clinical dermatology. However, model opacity and the lack o…

cs.CV2025

Jigsaw3D: Disentangled 3D Style Transfer via Patch Shuffling and Masking

Yuteng Ye, Zheng Zhang, Qinchuan Zhang +5

Controllable 3D style transfer seeks to restyle a 3D asset so that its textures match a reference image while preserving the integrity and multi-view consistency. The prevalent met…

cs.CV2025

OpenUrban3D: Annotation-Free Open-Vocabulary Semantic Segmentation of Large-Scale Urban Point Clouds

Chongyu Wang, Kunlei Jing, Jihua Zhu +1

Open-vocabulary semantic segmentation enables models to recognize and segment objects from arbitrary natural language descriptions, offering the flexibility to handle novel, fine-g…

cs.CV2025

HunyuanWorld 1.0: Generating Immersive, Explorable, and Interactive 3D Worlds from Words or Pixels

HunyuanWorld Team, Zhenwei Wang, Yuhao Liu +52

Creating immersive and playable 3D worlds from texts or images remains a fundamental challenge in computer vision and graphics. Existing world generation approaches typically fall…

cs.CV2025

Robust and Efficient 3D Gaussian Splatting for Urban Scene Reconstruction

Zhensheng Yuan, Haozhi Huang, Zhen Xiong +2

We present a framework that enables fast reconstruction and real-time rendering of urban-scale scenes while maintaining robustness against appearance variations across multi-view c…

cs.CV2025

X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again

Zigang Geng, Yibing Wang, Yeyao Ma +10

Numerous efforts have been made to extend the ``next token prediction'' paradigm to visual contents, aiming to create a unified approach for both image generation and understanding…

cs.CV2025

Hunyuan-Game: Industrial-grade Intelligent Game Creation Model

Ruihuang Li, Caijin Zhou, Shoujian Zheng +55

Intelligent game creation represents a transformative advancement in game development, utilizing generative artificial intelligence to dynamically generate and enhance game content…

cs.CL2025

Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought

Tencent Hunyuan Team, Ao Liu, Botong Zhou +248

As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…

cs.CV2025

SyncAnimation: A Real-Time End-to-End Framework for Audio-Driven Human Pose and Talking Head Animation

Yujian Liu, Shidang Xu, Jing Guo +4

Generating talking avatar driven by audio remains a significant challenge. Existing methods typically require high computational costs and often lack sufficient facial detail and r…

cs.CV2025★ 9 cited

Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

Zibo Zhao, Zeqiang Lai, Qingxiang Lin +71

We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two foundation components: a large-sca…

cs.CV2024

Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation

Xianghui Yang, Huiwen Shi, Bowen Zhang +20

While 3D generative models have greatly improved artists' workflows, the existing diffusion models for 3D generation suffer from slow generation and poor generalization. To address…