14 citations · 43 across the 15 of their papers we have counts for
15 papers
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…
AnyCharV: Bootstrap Controllable Character Video Generation with Fine-to-Coarse Guidance
Zhao Wang, Hao Wen, Lingting Zhu +3
Character video generation is a significant real-world application focused on producing high-quality videos featuring specific characters. Recent advancements have introduced vario…
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…
CustomVideo: Customizing Text-to-Video Generation with Multiple Subjects
Zhao Wang, Aoxue Li, Lingting Zhu +3
Customized text-to-video generation aims to generate high-quality videos guided by text prompts and subject references. Current approaches for personalizing text-to-video generatio…
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…
Cheap Lunch for Medical Image Segmentation by Fine-tuning SAM on Few Exemplars
Weijia Feng, Lingting Zhu, Lequan Yu
The Segment Anything Model (SAM) has demonstrated remarkable capabilities of scaled-up segmentation models, enabling zero-shot generalization across a variety of domains. By levera…
Make-A-Volume: Leveraging Latent Diffusion Models for Cross-Modality 3D Brain MRI Synthesis
Lingting Zhu, Zeyue Xue, Zhenchao Jin +4
Cross-modality medical image synthesis is a critical topic and has the potential to facilitate numerous applications in the medical imaging field. Despite recent successes in deep-…
Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation
Lingting Zhu, Xian Liu, Xuanyu Liu +3
Animating virtual avatars to make co-speech gestures facilitates various applications in human-machine interaction. The existing methods mainly rely on generative adversarial netwo…