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Knowledge-aware video recommendation requires the ability of associating external knowledge to capture high-order connectivities between users and videos. One limitation of existing methods is that they only extract user interests at a granular level of ...

LiDAR super-resolution can improve the quality of point cloud data, which is critical for improving many downstream tasks such as object detection, identification, and tracking. Traditional LiDAR super-resolution models often struggle with issues ...

In the field of computer vision, many perception methods rely on depth information captured by depth cameras. However, the integrity of depth maps is hindered by the reflection and refraction of light on transparent objects. Existing methods of ...

Multi-modal large language models (MLLMs), such as GPT-4, exhibit great comprehension capabilities on human instruction, as well as zero-shot ability on new downstream multi-modal tasks. To integrate the different modalities within a unified embedding ...

With the booming of streaming media platforms, viewers now get used to watching dramas and movies via online platforms with more intelligent services. Usually, character relationships may dynamically evolve with stories promoting in long videos. Therefore,...

People enjoy sharing "notes" including their experiences within online communities. Therefore, recommending notes aligned with user interests has become a crucial task. Existing online methods only input notes into BERT-based models to generate note ...

The assessment of Chinese essays with respect to text coherence using deep learning has been relatively understudied due to the lack of large-scale, high-quality discourse coherence evaluation data resources. Existing research predominantly ...

To solve the bottleneck of amplitude and phase accuracy deterioration caused by process and unpredictable errors, this paper proposes a Ku-band common-leg transceiver with built-in configurable register to achieve 64-state amplitude ...

Multiple laser stripe measurement (MLSM) is a vital technique in optical three-dimensional (3D) measurement. The accurate extraction of the laser stripe centerlines plays a decisive role in achieving high measurement accuracy. However, complex 3D ...

Recent years have witnessed the booming of online social media platforms with embracing the popular service called “Time-Sync Comment”, which supports the viewers to share their time-sync opinions along with video content. In this way, we observe that ...

Multimodal entity linking (MEL) task, which aims at resolving ambiguous mentions to a multimodal knowledge graph, has attracted wide attention in recent years. Though large efforts have been made to explore the complementary effect among multiple ...

As a widely studied topic in recommender systems, collaborative filtering (CF) methods help users discover potential items of interest by assuming that behavioral similar users would have similar preferences on items. A recent trend is to develop models ...

Understanding the long duration videos' storyline is often considered a major challenge in the field of video understanding. To promote research on understanding longer videos in the community, the deep video understanding (DVU) task is suggested for ...

Knowledge Graph Completion (KGC), aiming to infer the missing part of Knowledge Graphs (KGs), has long been treated as a crucial task to support downstream applications of KGs, especially for the multimodal KGs (MKGs) which suffer the incomplete ...

Automatic modulation recognition (AMR) plays an essential role in wireless communication systems. Our paper proposes a novel multi-stream neural network (MSNN) to extract the features in parallel from the amplitude, phase, frequency, ...

The retrieval question-answering(Q&A) system based on Q&A library is a system that can retrieve the most similar question from Q&A library to get the correct answer. Classic approaches only use TF-IDF, BM25 and other algorithms to calculate the shallow ...

Recent years have witnessed the booming of online video platforms. Along this line, a graph to illustrate social relation among characters has been long expected to not only benefit the audiences for better understanding the story, but also support the ...

To train accurate deep object detectors under the extreme foreground-background imbalance, heuristic sampling methods are always necessary, which either re-sample a subset of all training samples (hard sampling methods, <italic>e.g.</italic> biased ...

Advanced technologies are producing large-scale protein-protein interaction data at an ever increasing pace. Finding protein-protein interaction complexes from large PPI networks is a fundamental problem in bioinformatics. As a group of core proteins ...