1 citations · 1 across the 14 of their papers we have counts for
14 papers
GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions
Chenghao Gu, Hanyang Yu, Jingbo Zhang +7
Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning and evaluation in diverse rea…
MesonGS++: Post-training Compression of 3D Gaussian Splatting with Hyperparameter Searching
Shuzhao Xie, Junchen Ge, Weixiang Zhang +10
3D Gaussian Splatting (3DGS) achieves high-quality novel view synthesis with real-time rendering, but its storage cost remains prohibitive for practical deployment. Existing post-t…
VGGT-DP: Generalizable Robot Control via Vision Foundation Models
Shijia Ge, Yijun Liu, Yinxin Zhang +4
Visual imitation learning frameworks allow robots to learn manipulation skills from expert demonstrations. While existing approaches mainly focus on policy design, they often negle…
Music-Aligned Holistic 3D Dance Generation via Hierarchical Motion Modeling
Xiaojie Li, Ronghui Li, Shukai Fang +5
Well-coordinated, music-aligned holistic dance enhances emotional expressiveness and audience engagement. However, generating such dances remains challenging due to the scarcity of…
SD-GS: Structured Deformable 3D Gaussians for Efficient Dynamic Scene Reconstruction
Wei Yao, Shuzhao Xie, Letian Li +5
Current 4D Gaussian frameworks for dynamic scene reconstruction deliver impressive visual fidelity and rendering speed, however, the inherent trade-off between storage costs and th…
Lungmix: A Mixup-Based Strategy for Generalization in Respiratory Sound Classification
Shijia Ge, Weixiang Zhang, Shuzhao Xie +2
Respiratory sound classification plays a pivotal role in diagnosing respiratory diseases. While deep learning models have shown success with various respiratory sound datasets, our…
DragScene: Interactive 3D Scene Editing with Single-view Drag Instructions
Chenghao Gu, Zhenzhe Li, Zhengqi Zhang +3
3D editing has shown remarkable capability in editing scenes based on various instructions. However, existing methods struggle with achieving intuitive, localized editing, such as…
EVOS: Efficient Implicit Neural Training via EVOlutionary Selector
Weixiang Zhang, Shuzhao Xie, Chengwei Ren +5
We propose EVOlutionary Selector (EVOS), an efficient training paradigm for accelerating Implicit Neural Representation (INR). Unlike conventional INR training that feeds all sampl…
Enhancing Implicit Neural Representations via Symmetric Power Transformation
Weixiang Zhang, Shuzhao Xie, Chengwei Ren +3
We propose symmetric power transformation to enhance the capacity of Implicit Neural Representation~(INR) from the perspective of data transformation. Unlike prior work utilizing r…
Staleness-Centric Optimizations for Parallel Diffusion MoE Inference
Jiajun Luo, Lizhuo Luo, Jianru Xu +4
Mixture-of-Experts-based (MoE-based) diffusion models demonstrate remarkable scalability in high-fidelity image generation, yet their reliance on expert parallelism introduces crit…
MesonGS: Post-training Compression of 3D Gaussians via Efficient Attribute Transformation
Shuzhao Xie, Weixiang Zhang, Chen Tang +4
3D Gaussian Splatting demonstrates excellent quality and speed in novel view synthesis. Nevertheless, the huge file size of the 3D Gaussians presents challenges for transmission an…
Expansive Supervision for Neural Radiance Field
Weixiang Zhang, Shuzhao Xie, Shijia Ge +3
Neural Radiance Field (NeRF) has achieved remarkable success in creating immersive media representations through its exceptional reconstruction capabilities. However, the computati…
A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
Jiajun Song, Jiajun Luo, Rongwei Lu +3
Asynchronous Federated Learning (AFL) confronts inherent challenges arising from the heterogeneity of devices (e.g., their computation capacities) and low-bandwidth environments, b…
Tuning-Free Visual Customization via View Iterative Self-Attention Control
Xiaojie Li, Chenghao Gu, Shuzhao Xie +3
Fine-Tuning Diffusion Models enable a wide range of personalized generation and editing applications on diverse visual modalities. While Low-Rank Adaptation (LoRA) accelerates the…