Trustworthy AI: From principles to practices
The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …
of various systems based on it. However, many current AI systems are found vulnerable to …
The elements of end-to-end deep face recognition: A survey of recent advances
Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …
vision. With the recent development of deep learning techniques and large-scale datasets …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Webface260m: A benchmark unveiling the power of million-scale deep face recognition
In this paper, we contribute a new million-scale face benchmark containing noisy 4M
identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) …
identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) …
Graph clustering with graph neural networks
Graph Neural Networks (GNNs) have achieved state-of-the-art results on many graph
analysis tasks such as node classification and link prediction. However, important …
analysis tasks such as node classification and link prediction. However, important …
Online deep clustering for unsupervised representation learning
Joint clustering and feature learning methods have shown remarkable performance in
unsupervised representation learning. However, the training schedule alternating between …
unsupervised representation learning. However, the training schedule alternating between …
Learning a proposal classifier for multiple object tracking
P Dai, R Weng, W Choi, C Zhang… - Proceedings of the …, 2021 - openaccess.thecvf.com
The recent trend in multiple object tracking (MOT) is heading towards leveraging deep
learning to boost the tracking performance. However, it is not trivial to solve the data …
learning to boost the tracking performance. However, it is not trivial to solve the data …
Semanticadv: Generating adversarial examples via attribute-conditioned image editing
Recent studies have shown that DNNs are vulnerable to adversarial examples which are
manipulated instances targeting to mislead DNNs to make incorrect predictions. Currently …
manipulated instances targeting to mislead DNNs to make incorrect predictions. Currently …
Graph representation learning meets computer vision: A survey
A graph structure is a powerful mathematical abstraction, which can not only represent
information about individuals but also capture the interactions between individuals for …
information about individuals but also capture the interactions between individuals for …
Robust image clustering via context-aware contrastive graph learning
Graph convolution networks (GCN) have recently become popular for image clustering.
However, existing GCN-based image clustering techniques focus on learning image …
However, existing GCN-based image clustering techniques focus on learning image …