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Multimodal sentiment analysis is an important area for understanding the user's internal states. Deep learning methods were effective, but the problem of poor interpretability has gradually gained attention. Previous works have attempted to…

Computation and Language · Computer Science 2023-05-15 Sixia Li , Shogo Okada

Production-level workflows for producing convincing 3D dynamic human faces have long relied on an assortment of labor-intensive tools for geometry and texture generation, motion capture and rigging, and expression synthesis. Recent neural…

Computer Vision and Pattern Recognition · Computer Science 2022-09-19 Longwen Zhang , Chuxiao Zeng , Qixuan Zhang , Hongyang Lin , Ruixiang Cao , Wei Yang , Lan Xu , Jingyi Yu

Recent years have witnessed many advancements in the applications of 3D textured meshes. As the demand continues to rise, evaluating the perceptual quality of this new type of media content becomes crucial for quality assurance and…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Armin Shafiee Sarvestani , Wei Zhou , Zhou Wang

Change detection is a fundamental task in computer vision. Despite significant advances have been made, most of the change detection methods fail to work well in challenging scenes due to ubiquitous noise and interferences. Nowadays,…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Dawei Li , Siyuan Yan , Xin Cai , Yan Cao , Sifan Wang

The fundamental quantity governing the mechanical and thermodynamic properties of a crystalline solid is its electronic charge density. Yet, its direct use for the rapid prediction of materials properties remains challenging due to its high…

Materials Science · Physics 2026-05-11 Kammampati Sai Kumar , Albert Linda , Shubham Kumar Maurya , Somnath Bhowmick

Generative AI models offer powerful capabilities but often lack transparency, making it difficult to interpret their output. This is critical in cases involving artistic or copyrighted content. This work introduces a search-inspired…

Artificial Intelligence · Computer Science 2025-04-03 Theodoros Aivalis , Iraklis A. Klampanos , Antonis Troumpoukis , Joemon M. Jose

We have recently seen great progress in learning interpretable music representations, ranging from basic factors, such as pitch and timbre, to high-level concepts, such as chord and texture. However, most methods rely heavily on music…

Machine Learning · Computer Science 2024-02-12 Xuanjie Liu , Daniel Chin , Yichen Huang , Gus Xia

In recent years, image generation has made great strides in improving the quality of images, producing high-fidelity ones. Also, quite recently, there are architecture designs, which enable GAN to unsupervisedly learn the semantic…

Computer Vision and Pattern Recognition · Computer Science 2022-08-10 Xin Jin , Shu Zhao , Le Zhang , Xin Zhao , Qiang Deng , Chaoen Xiao

Adapting pre-trained foundation models for various downstream tasks has been prevalent in artificial intelligence. Due to the vast number of tasks and high costs, adjusting all parameters becomes unfeasible. To mitigate this, several…

Computer Vision and Pattern Recognition · Computer Science 2025-02-07 Chongjie Si , Xuehui Wang , Xue Yang , Zhengqin Xu , Qingyun Li , Jifeng Dai , Yu Qiao , Xiaokang Yang , Wei Shen

Human visual system has the strong ability to quick assess the perceptual similarity between two facial sketches. However, existing two widely-used facial sketch metrics, e.g., FSIM and SSIM fail to address this perceptual similarity in…

Computer Vision and Pattern Recognition · Computer Science 2019-09-05 Deng-Ping Fan , ShengChuan Zhang , Yu-Huan Wu , Yun Liu , Ming-Ming Cheng , Bo Ren , Paul L. Rosin , Rongrong Ji

A critical aspect of human visual perception is the ability to parse visual scenes into individual objects and further into object parts, forming part-whole hierarchies. Such composite structures could induce a rich set of semantic concepts…

Computer Vision and Pattern Recognition · Computer Science 2021-12-10 Yining Hong , Li Yi , Joshua B. Tenenbaum , Antonio Torralba , Chuang Gan

Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks, making it difficult to generalize across different but…

For the last decade, convolutional neural networks (CNNs) have vastly superseded their predecessors in nearly all vision tasks in artificial intelligence, including object recognition. However, despite abundant advancements, they continue…

Computer Vision and Pattern Recognition · Computer Science 2023-02-09 Brandon RichardWebster , Justin Dulay , Anthony DiFalco , Elisabetta Caldesi , Walter J. Scheirer

Generating portrait images by controlling the motions of existing faces is an important task of great consequence to social media industries. For easy use and intuitive control, semantically meaningful and fully disentangled parameters…

Computer Vision and Pattern Recognition · Computer Science 2021-09-20 Yurui Ren , Ge Li , Yuanqi Chen , Thomas H. Li , Shan Liu

Multimodal clothing image editing refers to the precise adjustment and modification of clothing images using data such as textual descriptions and visual images as control conditions, which effectively improves the work efficiency of…

Computer Vision and Pattern Recognition · Computer Science 2024-09-24 Di Cheng , YingJie Shi , ShiXin Sun , JiaFu Zhang , WeiJing Wang , Yu Liu

Autonomously exploring the unknown physical properties of novel objects such as stiffness, mass, center of mass, friction coefficient, and shape is crucial for autonomous robotic systems operating continuously in unstructured environments.…

Robotics · Computer Science 2024-05-24 Anirvan Dutta , Etienne Burdet , Mohsen Kaboli

Robotic fabric manipulation has applications in home robotics, textiles, senior care and surgery. Existing fabric manipulation techniques, however, are designed for specific tasks, making it difficult to generalize across different but…

We propose a novel methodology, forest floor, to visualize and interpret random forest (RF) models. RF is a popular and useful tool for non-linear multi-variate classification and regression, which yields a good trade-off between robustness…

Machine Learning · Statistics 2016-07-05 Soeren H. Welling , Hanne H. F. Refsgaard , Per B. Brockhoff , Line H. Clemmensen

Most visual quality inspections in discrete manufacturing are composed of length, surface, angle or intensity measurements. Those are implemented as end-user configurable inspection tools that should not require an image processing expert…

Computer Vision and Pattern Recognition · Computer Science 2013-10-02 Tomislav Petković , Darko Jurić , Sven Lončarić

Embodied perception systems face severe challenges of dynamic environment distribution drift when they continuously interact in open physical spaces. However, the existing domain incremental awareness methods often rely on the domain id…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Juncen Guo , Xiaoguang Zhu , Jingyi Wu , Jingyu Zhang , Jingnan Cai , Zhenghao Niu , Liang Song