AIMC Topic: Algorithms

Clear Filters Showing 12121 to 12130 of 28713 articles

Fast-GANFIT: Generative Adversarial Network for High Fidelity 3D Face Reconstruction.

IEEE transactions on pattern analysis and machine intelligence
A lot of work has been done towards reconstructing the 3D facial structure from single images by capitalizing on the power of deep convolutional neural networks (DCNNs). In the recent works, the texture features either correspond to components of a l...

Advanced Dropout: A Model-Free Methodology for Bayesian Dropout Optimization.

IEEE transactions on pattern analysis and machine intelligence
Due to lack of data, overfitting ubiquitously exists in real-world applications of deep neural networks (DNNs). We propose advanced dropout, a model-free methodology, to mitigate overfitting and improve the performance of DNNs. The advanced dropout t...

Line Graph Neural Networks for Link Prediction.

IEEE transactions on pattern analysis and machine intelligence
We consider the graph link prediction task, which is a classic graph analytical problem with many real-world applications. With the advances of deep learning, current link prediction methods commonly compute features from subgraphs centered at two ne...

Tweaking Deep Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
Deep neural networks are trained so as to achieve a kind of the maximum overall accuracy through a learning process using given training data. Therefore, it is difficult to fix them to improve the accuracies of specific problematic classes or classes...

Meta-Learning in Neural Networks: A Survey.

IEEE transactions on pattern analysis and machine intelligence
The field of meta-learning, or learning-to-learn, has seen a dramatic rise in interest in recent years. Contrary to conventional approaches to AI where tasks are solved from scratch using a fixed learning algorithm, meta-learning aims to improve the ...

Learning Layout and Style Reconfigurable GANs for Controllable Image Synthesis.

IEEE transactions on pattern analysis and machine intelligence
With the remarkable recent progress on learning deep generative models, it becomes increasingly interesting to develop models for controllable image synthesis from reconfigurable structured inputs. This paper focuses on a recently emerged task, layou...

Weakly Supervised Object Localization and Detection: A Survey.

IEEE transactions on pattern analysis and machine intelligence
As an emerging and challenging problem in the computer vision community, weakly supervised object localization and detection plays an important role for developing new generation computer vision systems and has received significant attention in the p...

Revisiting Light Field Rendering With Deep Anti-Aliasing Neural Network.

IEEE transactions on pattern analysis and machine intelligence
The light field (LF) reconstruction is mainly confronted with two challenges, large disparity and the non-Lambertian effect. Typical approaches either address the large disparity challenge using depth estimation followed by view synthesis or eschew e...

Robust Face Alignment via Deep Progressive Reinitialization and Adaptive Error-Driven Learning.

IEEE transactions on pattern analysis and machine intelligence
Regression-based face alignment involves learning a series of mapping functions to predict the true landmarks from an initial estimation of the alignment. Most existing approaches focus on learning efficacious mapping functions from some feature repr...

Active Fine-Tuning From gMAD Examples Improves Blind Image Quality Assessment.

IEEE transactions on pattern analysis and machine intelligence
The research in image quality assessment (IQA) has a long history, and significant progress has been made by leveraging recent advances in deep neural networks (DNNs). Despite high correlation numbers on existing IQA datasets, DNN-based models may be...