9 citations · 10 across the 10 of their papers we have counts for
11 papers
Are Text-to-Image Models Inductivist Turkeys? A Counterfactual Benchmark for Causal Reasoning
Jiayi Lei, Yuandong Pu, Xingyu Han +8
Text-to-image (T2I) generation models have achieved remarkable progress in producing visually realistic images from natural language prompts. Yet it remains unclear whether their s…
Motion-Aware Caching for Efficient Autoregressive Video Generation
Jing Xu, Yuexiao Ma, Xuzhe Zheng +7
Autoregressive video generation paradigms offer theoretical promise for long video synthesis, yet their practical deployment is hindered by the computational burden of sequential i…
MathGen: Revealing the Illusion of Mathematical Competence through Text-to-Image Generation
Ruiyao Liu, Hui Shen, Ping Zhang +16
Modern generative models have demonstrated the ability to solve challenging mathematical problems. In many real-world settings, however, mathematical solutions must be expressed vi…
Flow caching for autoregressive video generation
Yuexiao Ma, Xuzhe Zheng, Jing Xu +9
Autoregressive models, often built on Transformer architectures, represent a powerful paradigm for generating ultra-long videos by synthesizing content in sequential chunks. Howeve…
Perceptual Quality Assessment of 3D Gaussian Splatting: A Subjective Dataset and Prediction Metric
Zhaolin Wan, Yining Diao, Jingqi Xu +5
With the rapid advancement of 3D visualization, 3D Gaussian Splatting (3DGS) has emerged as a leading technique for real-time, high-fidelity rendering. While prior research has emp…
QuadGPT: Native Quadrilateral Mesh Generation with Autoregressive Models
Jian Liu, Chunshi Wang, Song Guo +9
The generation of quadrilateral-dominant meshes is a cornerstone of professional 3D content creation. However, existing generative models generate quad meshes by first generating t…
Auto-Connect: Connectivity-Preserving RigFormer with Direct Preference Optimization
Jingfeng Guo, Jian Liu, Jinnan Chen +9
We introduce Auto-Connect, a novel approach for automatic rigging that explicitly preserves skeletal connectivity through a connectivity-preserving tokenization scheme. Unlike prev…
Mesh-RFT: Enhancing Mesh Generation via Fine-grained Reinforcement Fine-Tuning
Jian Liu, Jing Xu, Song Guo +10
Existing pretrained models for 3D mesh generation often suffer from data biases and produce low-quality results, while global reinforcement learning (RL) methods rely on object-lev…
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…
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…
DragGaussian: Enabling Drag-style Manipulation on 3D Gaussian Representation
Sitian Shen, Jing Xu, Yuheng Yuan +3
User-friendly 3D object editing is a challenging task that has attracted significant attention recently. The limitations of direct 3D object editing without 2D prior knowledge have…