3 citations · 3 across the 13 of their papers we have counts for
15 papers
Unfold The World: Factorize 4D Properties in Reinforcing Spatial Reasoning
Yijun Yang, Shenghe Zheng, Wenbo Li +8
Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the physical world. We argue th…
ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training
Xionghao Wu, Yijun Yang, Shiyang Zhou +17
Robotic manipulation faces a fundamental scaling challenge: robust generalization demands broad physical experience, yet action-labeled robot trajectories are expensive to collect…
Fast Image Super-Resolution via Consistency Rectified Flow
Jiaqi Xu, Wenbo Li, Haoze Sun +8
Diffusion models (DMs) have demonstrated remarkable success in real-world image super-resolution (SR), yet their reliance on time-consuming multi-step sampling largely hinders thei…
JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation
Lin Song, Wenbo Li, Guoqing Ma +16
We present JoyAI-Image, a unified multimodal foundation model for visual understanding, text-to-image generation, and instruction-guided image editing. JoyAI-Image couples a spatia…
Geometry-Aware Neural Optimizer for Shape Optimization and Inversion
Guoze Sun, Tianya Miao, Haoyang Huang +4
Geometry is central to PDE-governed systems, motivating shape optimization and inversion. Classical pipelines conduct costly forward simulation with geometry processing, requiring…
Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence
Yanbing Zhang, Bo Wang, Jianhui Liu +9
Current Large Multimodal Models (LMMs) struggle with spatial reasoning tasks requiring viewpoint-dependent understanding, largely because they are confined to a single, static obse…
TextLDM: Language Modeling with Continuous Latent Diffusion
Jiaxiu Jiang, Jingjing Ren, Wenbo Li +10
Diffusion Transformers (DiT) trained with flow matching in a VAE latent space have unified visual generation across images and videos. A natural next step toward a single architect…
OpenSpatial: A Principled Data Engine for Empowering Spatial Intelligence
Jianhui Liu, Haoze Sun, Wenbo Li +11
Spatial understanding is a fundamental cornerstone of human-level intelligence. Nonetheless, current research predominantly focuses on domain-specific data production, leaving a cr…
PocketSR: The Super-Resolution Expert in Your Pocket Mobiles
Haoze Sun, Linfeng Jiang, Fan Li +9
Real-world image super-resolution (RealSR) aims to enhance the visual quality of in-the-wild images, such as those captured by mobile phones. While existing methods leveraging larg…
Turbo2K: Towards Ultra-Efficient and High-Quality 2K Video Synthesis
Jingjing Ren, Wenbo Li, Zhongdao Wang +9
Demand for 2K video synthesis is rising with increasing consumer expectations for ultra-clear visuals. While diffusion transformers (DiTs) have demonstrated remarkable capabilities…
Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling
Long Peng, Anran Wu, Wenbo Li +9
Arbitrary-scale super-resolution (ASSR) aims to reconstruct high-resolution (HR) images from low-resolution (LR) inputs with arbitrary upsampling factors using a single model, addr…
Beyond Pixels: Text Enhances Generalization in Real-World Image Restoration
Haoze Sun, Wenbo Li, Jiayue Liu +7
Generalization has long been a central challenge in real-world image restoration. While recent diffusion-based restoration methods, which leverage generative priors from text-to-im…
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution
Long Peng, Wenbo Li, Jiaming Guo +7
Real-world image super-resolution (Real SR) aims to generate high-fidelity, detail-rich high-resolution (HR) images from low-resolution (LR) counterparts. Existing Real SR methods…
Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning
Haoyu Chen, Wenbo Li, Jinjin Gu +6
For image super-resolution (SR), bridging the gap between the performance on synthetic datasets and real-world degradation scenarios remains a challenge. This work introduces a nov…
CoSeR: Bridging Image and Language for Cognitive Super-Resolution
Haoze Sun, Wenbo Li, Jianzhuang Liu +5
Existing super-resolution (SR) models primarily focus on restoring local texture details, often neglecting the global semantic information within the scene. This oversight can lead…