8 papers
Text-Image Conditioned 3D Generation
Jiazhong Cen, Jiemin Fang, Sikuang Li +8
High-quality 3D assets are essential for VR/AR, industrial design, and entertainment, motivating growing interest in generative models that create 3D content from user prompts. Mos…
AI Decodes Historical Chinese Archives to Reveal Lost Climate History
Sida He, Lingxi Xie, Xiaopeng Zhang +1
Historical archives contain qualitative descriptions of climate events, yet converting these into quantitative records has remained a fundamental challenge. Here we introduce a par…
Bridging the Gap Between Bayesian Deep Learning and Ensemble Weather Forecasts
Xinlei Xiong, Wenbo Hu, Shuxun Zhou +5
Weather forecasting is fundamentally challenged by the chaotic nature of the atmosphere, necessitating probabilistic approaches to quantify uncertainty. While traditional ensemble…
WorldGrow: Generating Infinite 3D World
Sikuang Li, Chen Yang, Jiemin Fang +6
We tackle the challenge of generating the infinitely extendable 3D world -- large, continuous environments with coherent geometry and realistic appearance. Existing methods face ke…
UniLat3D: Geometry-Appearance Unified Latents for Single-Stage 3D Generation
Guanjun Wu, Jiemin Fang, Chen Yang +11
High-fidelity 3D asset generation is crucial for various industries. While recent 3D pretrained models show strong capability in producing realistic content, most are built upon di…
Few-step Flow for 3D Generation via Marginal-Data Transport Distillation
Zanwei Zhou, Taoran Yi, Jiemin Fang +5
Flow-based 3D generation models typically require dozens of sampling steps during inference. Though few-step distillation methods, particularly Consistency Models (CMs), have achie…