14 citations · 21 across the 13 of their papers we have counts for
13 papers
Open-AoE: An Open Egocentric Manipulation Dataset and Toolchain for Embodied Learning
Zishuo Li, Bowen Yang, Changtao Miao +29
Egocentric videos of human manipulation provide scalable supervision for embodied intelligence, yet existing resources rarely combine low-cost continuous capture, manipulation-leve…
AssetFormer: Modular 3D Assets Generation with Autoregressive Transformer
Lingting Zhu, Shengju Qian, Haidi Fan +6
The digital industry demands high-quality, diverse modular 3D assets, especially for user-generated content~(UGC). In this work, we introduce AssetFormer, an autoregressive Transfo…
Large Material Gaussian Model for Relightable 3D Generation
Jingrui Ye, Lingting Zhu, Runze Zhang +5
The increasing demand for 3D assets across various industries necessitates efficient and automated methods for 3D content creation. Leveraging 3D Gaussian Splatting, recent large r…
AssetDropper: Asset Extraction via Diffusion Models with Reward-Driven Optimization
Lanjiong Li, Guanhua Zhao, Lingting Zhu +4
Recent research on generative models has primarily focused on creating product-ready visual outputs; however, designers often favor access to standardized asset libraries, a domain…
StyleAR: Customizing Multimodal Autoregressive Model for Style-Aligned Text-to-Image Generation
Yi Wu, Lingting Zhu, Shengju Qian +4
In the current research landscape, multimodal autoregressive (AR) models have shown exceptional capabilities across various domains, including visual understanding and generation.…
MuMA: 3D PBR Texturing via Multi-Channel Multi-View Generation and Agentic Post-Processing
Lingting Zhu, Jingrui Ye, Runze Zhang +8
Current methods for 3D generation still fall short in physically based rendering (PBR) texturing, primarily due to limited data and challenges in modeling multi-channel materials.…
Proxy-Tuning: Tailoring Multimodal Autoregressive Models for Subject-Driven Image Generation
Yi Wu, Shengju Qian, Lingting Zhu +5
Multimodal autoregressive (AR) models, based on next-token prediction and transformer architecture, have demonstrated remarkable capabilities in various multimodal tasks including…
Large Images are Gaussians: High-Quality Large Image Representation with Levels of 2D Gaussian Splatting
Lingting Zhu, Guying Lin, Jinnan Chen +4
While Implicit Neural Representations (INRs) have demonstrated significant success in image representation, they are often hindered by large training memory and slow decoding speed…
ToolBridge: An Open-Source Dataset to Equip LLMs with External Tool Capabilities
Zhenchao Jin, Mengchen Liu, Dongdong Chen +3
Through the integration of external tools, large language models (LLMs) such as GPT-4o and Llama 3.1 significantly expand their functional capabilities, evolving from elementary co…
Multi-sensor Learning Enables Information Transfer across Different Sensory Data and Augments Multi-modality Imaging
Lingting Zhu, Yizheng Chen, Lianli Liu +2
Multi-modality imaging is widely used in clinical practice and biomedical research to gain a comprehensive understanding of an imaging subject. Currently, multi-modality imaging is…
Generative Enhancement for 3D Medical Images
Lingting Zhu, Noel Codella, Dongdong Chen +3
The limited availability of 3D medical image datasets, due to privacy concerns and high collection or annotation costs, poses significant challenges in the field of medical imaging…
EndoGS: Deformable Endoscopic Tissues Reconstruction with Gaussian Splatting
Lingting Zhu, Zhao Wang, Jiahao Cui +3
Surgical 3D reconstruction is a critical area of research in robotic surgery, with recent works adopting variants of dynamic radiance fields to achieve success in 3D reconstruction…
IDRNet: Intervention-Driven Relation Network for Semantic Segmentation
Zhenchao Jin, Xiaowei Hu, Lingting Zhu +3
Co-occurrent visual patterns suggest that pixel relation modeling facilitates dense prediction tasks, which inspires the development of numerous context modeling paradigms, \emph{e…