1 citations · 1 across the 7 of their papers we have counts for
9 papers
PAWBench: How Far Are We from Probabilistically Aligned World Modeling?
Yuandong Pu, Le Zhuo, Sayak Paul +11
Recent video generation models are increasingly framed as world models. Many physical processes can unfold in more than one valid way. Therefore, a world model should reproduce not…
Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development
Zhongying Deng, Cheng Tang, Ziyan Huang +124
Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in…
Omni-Weather: A Unified Multimodal Model for Weather Radar Understanding and Generation
Zhiwang Zhou, Yuandong Pu, Xuming He +10
Weather modeling requires both accurate prediction and mechanistic interpretation, yet existing methods treat these goals in isolation, separating generation from understanding. To…
SynWeather: Weather Observation Data Synthesis across Multiple Regions and Variables via a General Diffusion Transformer
Kaiyi Xu, Junchao Gong, Zhiwang Zhou +7
With the advancement of meteorological instruments, abundant data has become available. Current approaches are typically focus on single-variable, single-region tasks and primarily…
PICABench: How Far Are We from Physically Realistic Image Editing?
Yuandong Pu, Le Zhuo, Songhao Han +10
Image editing has achieved remarkable progress recently. Modern editing models could already follow complex instructions to manipulate the original content. However, beyond complet…
Exploring Scalable Unified Modeling for General Low-Level Vision
Xiangyu Chen, Kaiwen Zhu, Yuandong Pu +7
Low-level vision involves a wide spectrum of tasks, including image restoration, enhancement, stylization, and feature extraction, which differ significantly in both task formulati…
Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision
Yuandong Pu, Le Zhuo, Kaiwen Zhu +7
We present Lunima-OmniLV (abbreviated as OmniLV), a universal multimodal multi-task framework for low-level vision that addresses over 100 sub-tasks across four major categories: i…
A Preliminary Exploration Towards General Image Restoration
Xiangtao Kong, Jinjin Gu, Yihao Liu +4
Despite the tremendous success of deep models in various individual image restoration tasks, there are at least two major technical challenges preventing these works from being app…
GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity
Shuo Cao, Yihao Liu, Wenlong Zhang +2
Traditional single-task image restoration methods excel in handling specific degradation types but struggle with multiple degradations. To address this limitation, we propose Group…