Abstract: The promotion of the HEVC standard has significantly alleviated the burden of network transmission and video storage. However, its inherent complexity and data dependencies pose a ...
Abstract: Unsupervised anomaly detection (UAD) aims to recognize anomalous images based on the training set that contains only normal images. In medical image analysis, UAD benefits from leveraging ...
Abstract: Considering the impact of operation and maintenance costs and technology, there is generally a lack of sufficient meteorological observation devices within the distributed photovoltaic (PV) ...
Abstract: Instantaneous angular speed (IAS) signals are widely used in motor control and fault detection. However, incremental optical encoders inevitably suffer from engraving and subdivision errors ...
Abstract: DETR first used a transformer in object detection. It does not use anchor boxes and non-maximum suppression by converting object detection into a set prediction problem. DETR has shown ...
Official repository for the paper "Exploring the Potential of Encoder-free Architectures in 3D LMMs". The encoder-free 3D LMM directly utilizes a token embedding module to convert point cloud data ...
Abstract: With the prevalence of thermal cameras, RGB-T multi-modal data have become more available for salient object detection (SOD) in complex scenes. Most RGB-T SOD works first individually ...
Abstract: Point-interactive image colorization is intended to colorize a grayscale image by allowing the user to specify colors at specific locations. The colors provided by the user (user hints) are ...
Abstract: Multi-modal data presents a promising opportunity for improving multimedia recommendation models, but it also introduces task-irrelevant noise that can reduce model robustness. In this paper ...
Abstract: High Efficiency Video Coding (HEVC) and Multi-access Edge Computing (MEC) technologies can make real-time streaming media services available to users with reasonable bandwidth, but the ...
Abstract: Convolutional neural networks (CNNs) have attracted much attention in change detection (CD) for their superior feature learning ability. However, most of the existing CNN-based CD methods ...
Abstract: Image anomaly detection problems aim to determine whether an image is abnormal, and to detect anomalous areas. These methods are actively used in various fields such as manufacturing, ...
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