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: 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 ...
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: 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: This article presents a new deep-learning architecture based on an encoder-decoder framework that retains contrast while performing background subtraction (BS) on thermal videos. The ...
Abstract: This paper presents an absolute capacitive rotary encoder using a sample-and-hold demodulator (SHD) to reduce interference between sine and cosine channels. The capacitive encoder measures ...
This video tutorial demonstrates how to use and leverage 3 key new features found under the Effects tab in Adobe Media Encoder CC (which replaces the much more limited Filters tab in Adobe Media ...
Abstract: Infrared small target detection (IRSTD) is the challenging task of identifying small targets with low signal-to-noise ratios in complex backgrounds. Traditional methods in the complex ...
Abstract: Benefiting from the powerful feature extraction and feature correlation modeling capabilities of convolutional neural networks (CNNs) and Transformer models, these techniques have been ...
Abstract: With the growing popularity of high-resolution (HR) video and the continuous growth of network bandwidth, the challenge of object removal detection in HR videos has attracted significant ...