6 papers
UGOD: Uncertainty-Guided Opacity and Dropout for Sparse-View 3D Gaussian Splatting
Zhihao Guo, Peng Wang, Zidong Chen +7
Sparse-view 3D Gaussian Splatting is prone to overfitting because limited observations leave many Gaussian primitives weakly constrained, yet their contributions are still accumula…
Dense-Jump Flow Matching with Non-Uniform Time Scheduling for Robotic Policies: Mitigating Multi-Step Inference Degradation
Zidong Chen, Zihao Guo, Peng Wang +3
Flow matching has emerged as a competitive framework for learning high-quality generative policies in robotics; however, we find that generalisation arises and saturates early alon…
UGOD: Uncertainty-Guided Differentiable Opacity and Soft Dropout for Enhanced Sparse-View 3DGS
Zhihao Guo, Peng Wang, Zidong Chen +4
3D Gaussian Splatting (3DGS) has become a competitive approach for novel view synthesis (NVS) due to its advanced rendering efficiency through 3D Gaussian projection and blending.…
COLI: A Hierarchical Efficient Compressor for Large Images
Haoran Wang, Hanyu Pei, Yang Lyu +3
The escalating adoption of high-resolution, large-field-of-view imagery amplifies the need for efficient compression methodologies. Conventional techniques frequently fail to prese…
Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces
Yang Lyu, Tan Minh Nguyen, Yuchun Qian +1
Diffusion models are popular tools for generating new data samples, using a forward process that adds noise to data and a reverse process to denoise and produce samples. However, w…
Personalized Federated Learning via Learning Dynamic Graphs
Ziran Zhou, Guanyu Gao, Xiaohu Wu +1
Personalized Federated Learning (PFL) aims to train a personalized model for each client that is tailored to its local data distribution, learning fails to perform well on individu…