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Dynamic reconstruction of deformable tissues in endoscopic video is a key technology for robot-assisted surgery. Recent reconstruction methods based on neural radiance fields (NeRFs) have achieved remarkable results in the reconstruction of ...

Power grid analysis is essential for integrated circuit design, especially as the scale extends to billions of nodes, making precise calculations across the entire spatial domain prohibitively expensive. Domain decomposition methods (DDM) facilitate ...

Chiplet has recently emerged as a promising solution to achieving further performance improvements by breaking down complex processors into modular components and communicating through high-speed inter-chiplet serial links. However, the ever-growing on-...

With the growth of demand for air-space integrated transportation industry, the civil aviation transportation industry plays an increasingly important role in the national economy and transportation. The diversity and diversified development of ...

Existing research primarily focuses on spelling and grammatical errors in English, such as missing or wrongly adding characters. This kind of shallow error has been well-studied. Instead, there are many unsolved deep-level errors in real ...

Supervoxel segmentation for video is a video pre-processing technique that groups voxels with similar spatiotemporal features into supervoxels, effectively reducing the number of elemental voxels for downstream computer vision applications, or ...

• To mitigate the negative effects on feature transferability resulting from the strong constraint of GD and modeling procedure of GD resulting from wrongly ...

Domain adaptation (DA) is a powerful technology that allows a classifier trained on a well-labeled source domain to be adapted to an unlabeled target domain with different distributions. Existing DA methods aim to enhance feature ...

Style transfer is a popular research topic in the field of computer vision. In 3D stylization, a mesh model is deformed to achieve a specific geometric style. We explore a general neural style transfer framework for 3D meshes that can ...

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Emotional support conversation aims to provide comfort and suggestions to users and gradually reduce their negative emotions such as anxiety. It is a valuable topic for many applications, including mental health support and customer service chats. ...

This paper proposes a new task of Multi-modal Multi-emotion Emotional Support Conversation (MMESC), which has great value in various applications, such as counseling, daily chatting, and elderly company. This task aims to fully perceive the users’ ...

Transformers have been widely applied in various vision tasks processing different data, such as images, videos and point clouds. However, the use of transformers in 3D mesh analysis remains largely unexplored. To address this gap, we propose a ...

Our goal in this research is to study a more realistic environment in which we can conduct weakly-supervised multi-modal instance-level product retrieval for fine-grained product categories. We first contribute the Product1M datasets and define two real ...

Unsupervised multi-view feature selection aims to select informative features with multi-view features and unsupervised learning. It is a challenging problem due to the absence of explicit semantic supervision. Recently, graph theory and hard pseudo-label ...

Power integrity analysis is an essential step in power distribution network (PDN) sign-off to ensure the performance and reliability of chips. However, with the growing PDN size and increasing scenarios to be validated, it becomes very time- and resource-...

Aiming at the multiband pattern synthesis problem of time-modulated conformal array antenna, a quadratic convex optimization algorithm is proposed for sum and difference beamforming with low sidelobe levels. This articles method synthesizes a difference ...

Product detection, which aims to localize products of interest in the advertising images, helps advance many potential E-commerce applications like product retrieval and recommendation. However, labeling a massive number of fine-grained product categories ...

Hashing techniques have attracted considerable attention owing to their advantages of efficient computation and economical storage. However, it is still a challenging problem to generate more compact binary codes for promising performance. In this ...

Commonsense question answering requires reasoning about everyday situations and causes and effects implicit in context. Typically, existing approaches first retrieve external evidence and then perform commonsense reasoning using these evidence. ...

• A self-supervised learning method is proposed to solve commonsense QA task.
• A novel CRL task and a JP task are presented to facilitate commonsense learning.
• Experiments verify that elBERTo significantly outperforms the existing ...

Deep Neural Networks (DNNs) tend to go deeper and wider, which poses a significant challenge to the training of DNNs, due to the limited memory capacity of DNN accelerators. Existing solutions for memory-efficient DNN training are densely coupled with the ...

Worst-case dynamic PDN noise analysis is an essential step in PDN sign-off to ensure the performance and reliability of chips. However, with the growing PDN size and increasing scenarios to be validated, it becomes very time- and resource-consuming to ...