Search Results for author:
Found 20 papers, 2 papers with code
EGGS: Edge Guided Gaussian Splatting for Radiance Fields
Therefore, in this paper, we propose an Edge Guided Gaussian Splatting (EGGS) method that leverages the edges in the input images.
Isotropic Gaussian Splatting for Real-Time Radiance Field Rendering
The 3D Gaussian splatting method has drawn a lot of attention, thanks to its high performance in training and high quality of the rendered image.
P2I-NET: Mapping Camera Pose to Image via Adversarial Learning for New View Synthesis in Real Indoor Environments
Given a new $6DoF$ camera pose in an indoor environment, we study the challenging problem of predicting the view from that pose based on a set of reference RGBD views.
PLMM: Personal Large Models on Mobile Devices
We classify the large language models into three levels: the personal level, expert level and traditional level.
Gradient Domain Diffusion Models for Image Synthesis
Several numerical experiments confirm that the gradient domain diffusion models are more efficient than the original diffusion models.
TSSR: A Truncated and Signed Square Root Activation Function for Neural Networks
Thanks to these properties, it has the potential to improve the numerical stability of neural networks.
STL: A Signed and Truncated Logarithm Activation Function for Neural Networks
Activation functions play an essential role in neural networks.
Multilevel Large Language Models for Everyone
Such behavior on human brain cortex sheds the light to design the multilevel large language models that contain global level, field level and user level models.
Dynamic Large Language Models on Blockchains
Training and deploying the large language models requires a large mount of computational resource because the language models contain billions of parameters and the text has thousands of tokens.
One-Sided Box Filter for Edge Preserving Image Smoothing
In this paper, we present a one-sided box filter that can smooth the signal but keep the discontinuous features in the signal.
Quarter Laplacian Filter for Edge Aware Image Processing
The proposed filter can be adopted in a wide range of image processing applications.
A Discrete Scheme for Computing Image's Weighted Gaussian Curvature
Weighted Gaussian Curvature is an important measurement for images.
A Residual Solver and Its Unfolding Neural Network for Total Variation Regularized Models
The proposed network is general and can be applied to solve other total variation regularized models.
Decompose X-ray Images for Bone and Soft Tissue
In this paper, we tackle this problem and propose a novel task to virtually decompose the soft tissue and bone by image processing algorithms.
Learning Deep Image Priors for Blind Image Denoising
In this paper, we propose an effective image denoising method by learning two image priors from the perspective of domain alignment.
Side Window Filtering
In addition to image filtering, we further show that the SWF principle can be extended to other applications involving the use of a local window.
HLO: Half-kernel Laplacian Operator for Surface Smoothing
This paper presents a simple yet effective method for feature-preserving surface smoothing.
Computational Geometry Graphics
Weighted Mean Curvature
In this paper, we introduce weighted mean curvature (WMC) as a novel image prior and present an efficient computation scheme for its discretization in practical image processing applications.
An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer Tissue Microarray
To the best of our knowledge, this is the first end-to-end system that takes a TMA image as input and directly outputs a clinical score.
Gradient Distribution Priors for Biomedical Image Processing
We provide motivation for this choice from different points of view, and we fully validate the resulting prior for use on biomedical images by showing its stability and correlation with image quality.
