Abstract: Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for ...
Abstract: Although the vision transformer-based methods (ViTs) exhibit an excellent performance than convolutional neural networks (CNNs) for image recognition tasks, their pixel-level semantic ...
Abstract: Sequential recommender systems seek to capture information about user affinities and behaviors considering their sequential series of interactions. While former models based on Markov Chains ...
Abstract: Light detection and ranging (LiDAR) point cloud denoising is critical for reliable environmental perception in autonomous driving and robotics. To overcome the lack of real-noise datasets ...
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) ...
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 ...