Search Results for author:
Found 45 papers, 14 papers with code
3D Reconstruction and New View Synthesis of Indoor Environments based on a Dual Neural Radiance Field
One of the innovative features of Du-NeRF is that it decouples a view-independent component from the density field and uses it as a label to supervise the learning process of the SDF field.
PSAvatar: A Point-based Morphable Shape Model for Real-Time Head Avatar Animation with 3D Gaussian Splatting
In this paper, we introduce PSAvatar, a novel framework for animatable head avatar creation that utilizes discrete geometric primitive to create a parametric morphable shape model and employs 3D Gaussian for fine detail representation and high fidelity rendering.
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.
Collaborative Auto-encoding for Blind Image Quality Assessment
Blind image quality assessment (BIQA) is a challenging problem with important real-world applications.
Aesthetically Relevant Image Captioning
Based on the observation that most textual comments of an image are about objects and their interactions rather than aspects of aesthetics, we first introduce the concept of Aesthetic Relevance Score (ARS) of a sentence and have developed a model to automatically label a sentence with its ARS.
ConvTransSeg: A Multi-resolution Convolution-Transformer Network for Medical Image Segmentation
We compared our method with many other state-of-the-art hybrid CNN and Transformer segmentation models on binary and multiple class image segmentation tasks using several public medical image datasets, including skin lesion, polyp, cell and brain tissue.
Improving Image Clustering through Sample Ranking and Its Application to remote--sensing images
Performing our method on a variety of datasets from remote sensing, we show that our method can be effectively applied to remote--sensing images.
Restoration of User Videos Shared on Social Media
This paper presents a new general video restoration framework for the restoration of user videos shared on social media platforms.
Lightness Modulated Deep Inverse Tone Mapping
Single-image HDR reconstruction or inverse tone mapping (iTM) is a challenging task.
Clustering-Based Representation Learning through Output Translation and Its Application to Remote--Sensing Images
In supervised deep learning, learning good representations for remote--sensing images (RSI) relies on manual annotations.
Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning
In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is designed to overcome the class imbalanced problem, and an active learning algorithm is introduced to significantly reduce the cost of labeling real-world data.
Super-resolving Compressed Images via Parallel and Series Integration of Artifact Reduction and Resolution Enhancement
Based on a mathematical inference model for estimating a clean low-resolution (LR) image and a clean high-resolution (HR) image from a down-sampled and compressed observation, we have designed a CISR architecture consisting of two deep neural network modules: the artefacts removal module (ARM) and the resolution enhancement module (REM).
A Discrete Scheme for Computing Image's Weighted Gaussian Curvature
Weighted Gaussian Curvature is an important measurement for images.
Quarter Laplacian Filter for Edge Aware Image Processing
The proposed filter can be adopted in a wide range of image processing applications.
VHS to HDTV Video Translation using Multi-task Adversarial Learning
In this paper, we focus on the problem of translating VHS video to HDTV video and have developed a solution based on a novel unsupervised multi-task adversarial learning model.
Deep Learning based Monocular Depth Prediction: Datasets, Methods and Applications
Despite the rapid progress in this topic, there are lacking of a comprehensive review, which is needed to summarize the current progress and provide the future directions.
Towards Disentangling Latent Space for Unsupervised Semantic Face Editing
In this paper, we present a new technique termed Structure-Texture Independent Architecture with Weight Decomposition and Orthogonal Regularization (STIA-WO) to disentangle the latent space for unsupervised semantic face editing.
MiniNet: An extremely lightweight convolutional neural network for real-time unsupervised monocular depth estimation
To the best of our knowledge, this work is the first extremely lightweight neural network trained on monocular video sequences for real-time unsupervised monocular depth estimation, which opens up the possibility of implementing deep learning-based real-time unsupervised monocular depth prediction on low-cost embedded devices.
Ranked #5 on
Semantic Segmentation
on SpectralWaste
PoseGAN: A Pose-to-Image Translation Framework for Camera Localization
We present PoseGANs, a conditional generative adversarial networks (cGANs) based framework for the implementation of pose-to-image translation.
Class-Aware Domain Adaptation for Improving Adversarial Robustness
To improve the adversarial robustness of neural networks, adversarial training has been proposed to train networks by injecting adversarial examples into the training data.
Discriminative Dimension Reduction based on Mutual Information
A widely used approach to tackling the problem is a group of subspace methods, where the original features are projected onto a new space.
Object Recognition with Human in the Loop Intelligent Frameworks
Classifiers embedded within human in the loop visual object recognition frameworks commonly utilise two sources of information: one derived directly from the imagery data of an object, and the other obtained interactively from user interactions.
Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation
The extensive experiments and ablation study demonstrate the effectiveness of our approach on the domain adaptive segmentation task.
Spectral Regularization for Combating Mode Collapse in GANs
Theoretical analysis shows that the optimal solution to the discriminator has a strong relationship to the spectral distributions of the weight matrix. Therefore, we monitor the spectral distribution in the discriminator of spectral normalized GANs (SN-GANs), and discover a phenomenon which we refer to as spectral collapse, where a large number of singular values of the weight matrices drop dramatically when mode collapse occurs.
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.
Improving Variational Autoencoder with Deep Feature Consistent and Generative Adversarial Training
We present a new method for improving the performances of variational autoencoder (VAE).
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
FrameRank: A Text Processing Approach to Video Summarization
In constructing the dataset, because of the subjectivity of user-generated video summarization, we manually annotate 25 summaries for each video, which are in total 1300 summaries.
Look, Investigate, and Classify: A Deep Hybrid Attention Method for Breast Cancer Classification
In this paper, we present a novel deep hybrid attention approach to breast cancer classification.
Enhancing Remote Sensing Image Retrieval with Triplet Deep Metric Learning Network
With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data.
End-to-End Single Image Fog Removal using Enhanced Cycle Consistent Adversarial Networks
In addition, we also contribute the first real world nature fog-fogfree image dataset for defogging research.
Relative Geometry-Aware Siamese Neural Network for 6DOF Camera Relocalization
6DOF camera relocalization is an important component of autonomous driving and navigation.
In-the-wild Facial Expression Recognition in Extreme Poses
In the computer research area, facial expression recognition is a hot research problem.
Facial Expression Recognition
Facial Expression Recognition (FER)
Lipschitz Constrained GANs via Boundedness and Continuity
In this paper, we introduce the boundedness and continuity ($BC$) conditions to enforce the Lipschitz constraint on the discriminator functions of GANs.
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.
Quality Classified Image Analysis with Application to Face Detection and Recognition
We will present experimental results to show that our quality classified framework can accurately classify images based on the type and severity of image degradations and can significantly boost the performances of state-of-the-art face detector and recognizer in dealing with image datasets containing mixed quality images.
Deep Feature Consistent Deep Image Transformations: Downscaling, Decolorization and HDR Tone Mapping
Building on crucial insights into the determining factors of the visual integrity of an image and the property of deep convolutional neural network (CNN), we have developed the Deep Feature Consistent Deep Image Transformation (DFC-DIT) framework which unifies challenging one-to-many mapping image processing problems such as image downscaling, decolorization (colour to grayscale conversion) and high dynamic range (HDR) image tone mapping.
Image Companding and Inverse Halftoning using Deep Convolutional Neural Networks
First, to the best knowledge of the authors, this is the first work that has successfully developed deep learning based solutions to these two traditional low-level image processing problems.
Deep Feature Consistent Variational Autoencoder
We present a novel method for constructing Variational Autoencoder (VAE).
Automatic Visual Theme Discovery from Joint Image and Text Corpora
Furthermore, not all tags have the same descriptive power for visual contents and large vocabulary available from natural language could result in a very diverse set of keywords.
Object Specific Deep Learning Feature and Its Application to Face Detection
We present a method for discovering and exploiting object specific deep learning features and use face detection as a case study.
Random Forest for Label Ranking
Label ranking aims to learn a mapping from instances to rankings over a finite number of predefined labels.
Supervised Learning and Anti-learning of Colorectal Cancer Classes and Survival Rates from Cellular Biology Parameters
For predicting the stage of cancer from the immunological attributes, anti-learning approaches outperform a range of popular algorithms.
Multi-scale Discriminant Saliency with Wavelet-based Hidden Markov Tree Modelling
Discriminant power of features for the classification is measured as mutual information between distributions of image features and corresponding classes .
