most citedHunyuan3D 2.1: From Images to High-Fidelity 3D Assets with Production-Ready PBR Material

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds

Team HY-World, Chenjie Cao, Xuhui Zuo +42

We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prom…

cs.CV2026

IDPruner: Harmonizing Importance and Diversity in Visual Token Pruning for MLLMs

Yifan Tan, Yifu Sun, Shirui Huang +4

Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities, yet they encounter significant computational bottlenecks due to the massive volume of visual tok…

cs.CV2025

Flash-DMD: Towards High-Fidelity Few-Step Image Generation with Efficient Distillation and Joint Reinforcement Learning

Guanjie Chen, Shirui Huang, Kai Liu +5

Diffusion Models have emerged as a leading class of generative models, yet their iterative sampling process remains computationally expensive. Timestep distillation is a promising…

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.CV20251 cited

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…