IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
This article presents a context-aware tracing strategy (CATS) for crisp edge detection with deep edge detectors, based on an observation that the localization ambiguity of deep edge detectors is mainly caused by the mixing phenomenon of convolutional...
IEEE transactions on pattern analysis and machine intelligence
Sep 14, 2022
Deep visual models are susceptible to adversarial perturbations to inputs. Although these signals are carefully crafted, they still appear noise-like patterns to humans. This observation has led to the argument that deep visual representation is misa...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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 ...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...
IEEE transactions on pattern analysis and machine intelligence
Aug 4, 2022
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...