4 citations · 13 across the 10 of their papers we have counts for
10 papers
-FedHT: Stepsize-Aware Hard-Threshold Gradient Compression in Federated Learning
Rongwei Lu, Yutong Jiang, Jinrui Zhang +4
Gradient compression can effectively alleviate communication bottlenecks in Federated Learning (FL). Contemporary state-of-the-art sparse compressors, such as Top-, exhibit high…
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…
An Efficient Implicit Neural Representation Image Codec Based on Mixed Autoregressive Model for Low-Complexity Decoding
Xiang Liu, Jiahong Chen, Bin Chen +4
Displaying high-quality images on edge devices, such as augmented reality devices, is essential for enhancing the user experience. However, these devices often face power consumpti…
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…
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization
Hao Fang, Bin Chen, Xuan Wang +2
Federated Learning (FL) has recently emerged as a promising distributed machine learning framework to preserve clients' privacy, by allowing multiple clients to upload the gradient…
One-stage Low-resolution Text Recognition with High-resolution Knowledge Transfer
Hang Guo, Tao Dai, Mingyan Zhu +4
Recognizing characters from low-resolution (LR) text images poses a significant challenge due to the information deficiency as well as the noise and blur in low-quality images. Cur…
Vision-Language Pre-training with Object Contrastive Learning for 3D Scene Understanding
Taolin Zhang, Sunan He, Dai Tao +3
In recent years, vision language pre-training frameworks have made significant progress in natural language processing and computer vision, achieving remarkable performance improve…
Instance-aware Dynamic Prompt Tuning for Pre-trained Point Cloud Models
Yaohua Zha, Jinpeng Wang, Tao Dai +3
Pre-trained point cloud models have found extensive applications in 3D understanding tasks like object classification and part segmentation. However, the prevailing strategy of ful…
Unsupervised Anomaly Detection with Local-Sensitive VQVAE and Global-Sensitive Transformers
Mingqing Wang, Jiawei Li, Zhenyang Li +4
Unsupervised anomaly detection (UAD) has been widely implemented in industrial and medical applications, which reduces the cost of manual annotation and improves efficiency in dise…