Computer Vision
Computer vision, a field focused on enabling computers to "see" and interpret images and videos, aims to develop algorithms that can perform tasks such as object detection, image classification, and scene understanding. Current research heavily utilizes deep learning, particularly convolutional neural networks (CNNs) and vision transformers (ViTs), often combined with techniques like multi-modal fusion (integrating data from different sensors) and transfer learning to improve efficiency and accuracy. These advancements are driving significant progress in diverse applications, including precision agriculture, robotics, medical imaging analysis, and autonomous systems, by providing automated, efficient, and objective solutions to complex visual tasks.
Papers - Page 13
Explainable Emotion Decoding for Human and Computer Vision
Alessio Borriero, Martina Milazzo, Matteo Diano, Davide Orsenigo, Maria Chiara Villa, Chiara Di Fazio, Marco Tamietto, Alan PerottiLa Sapienza University of Rome●University of Turin●Centai Institute●University of Camerino●Tilburg UniversityImproving Image De-raining Using Reference-Guided Transformers
Zihao Ye, Jaehoon Cho, Changjae OhQueen Mary University of London●Hyundai Motor Company
TiCoSS: Tightening the Coupling between Semantic Segmentation and Stereo Matching within A Joint Learning Framework
Guanfeng Tang, Zhiyuan Wu, Jiahang Li, Ping Zhong, Xieyuanli Chen, Huiming Lu, Rui FanMpox Detection Advanced: Rapid Epidemic Response Through Synthetic Data
Yudara Kularathne, Prathapa Janitha, Sithira Ambepitiya, Prarththanan Sothyrajah, Thanveer Ahamed, Dinuka Wijesundara
CHOSEN: Compilation to Hardware Optimization Stack for Efficient Vision Transformer Inference
Mohammad Erfan Sadeghi, Arash Fayyazi, Suhas Somashekar, Massoud PedramCerberusDet: Unified Multi-Dataset Object Detection
Irina Tolstykh, Mikhail Chernyshov, Maksim KuprashevichMotion and Structure from Event-based Normal Flow
Zhongyang Ren, Bangyan Liao, Delei Kong, Jinghang Li, Peidong Liu, Laurent Kneip, Guillermo Gallego, Yi Zhou