4 citations · 5 across the 6 of their papers we have counts for
6 papers
WATER-GS: Toward Copyright Protection for 3D Gaussian Splatting via Universal Watermarking
Yuqi Tan, Xiang Liu, Shuzhao Xie +3
3D Gaussian Splatting (3DGS) has emerged as a pivotal technique for 3D scene representation, providing rapid rendering speeds and high fidelity. As 3DGS gains prominence, safeguard…
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…
Invertible Residual Rescaling Models
Jinmin Li, Tao Dai, Yaohua Zha +6
Invertible Rescaling Networks (IRNs) and their variants have witnessed remarkable achievements in various image processing tasks like image rescaling. However, we observe that IRNs…
LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling
Yaohua Zha, Naiqi Li, Yanzi Wang +6
The pre-trained point cloud model based on Masked Point Modeling (MPM) has exhibited substantial improvements across various tasks. However, these models heavily rely on the Transf…
Towards Compact 3D Representations via Point Feature Enhancement Masked Autoencoders
Yaohua Zha, Huizhen Ji, Jinmin Li +5
Learning 3D representation plays a critical role in masked autoencoder (MAE) based pre-training methods for point cloud, including single-modal and cross-modal based MAE. Specifica…
Data-Aware Gradient Compression for FL in Communication-Constrained Mobile Computing
Rongwei Lu, Yutong Jiang, Yinan Mao +4
Federated Learning (FL) in mobile environments faces significant communication bottlenecks. Gradient compression has proven as an effective solution to this issue, offering substan…