Daniel Cores Costa

Daniel Cores Costa is an Associate Professor of Computer Science and Artificial Intelligence at the University of Santiago de Compostela (USC) and a researcher at the Research Center on Intelligent Technologies (CiTIUS). He completed his PhD in Research in Technologies in November 2022 with a dissertation on 'Spatio-temporal convolutional neural networks for video object detection' under the supervision of Victor Manuel Brea Sanchez.

Dr. Cores Costa's research focuses on computer vision with specialized expertise in several interconnected areas:

• Video object detection leveraging spatio-temporal information
• Small object detection challenges
• Advancing few-shot learning techniques for object detection with limited training data
• Developing open-vocabulary and category-free detection approaches
• Practical applications in medical imaging (particularly COVID-19 diagnosis) and UAV technology

His recent publications (2023-2025) demonstrate a strong research trajectory with multiple first-author papers in top venues including ICCV, BMVC, and CAIP, as well as high-impact journals. Dr. Cores Costa's work consistently addresses fundamental challenges in object detection while developing practical solutions for real-world applications across various domains.

Key contributions include:

• Development of the Downsampling GAN for small object data augmentation
• Innovative approaches to few-shot object detection through pseudo-label mining (xPAND)
• Pioneering work on category-free detection using open-vocabulary models
• Creation of TVBench, a new temporal benchmark for video-language models
• Advancements in spatiotemporal tubelet feature aggregation for small object detection

Dr. Cores Costa actively collaborates with researchers both within USC and internationally, as evidenced by his diverse co-authorship patterns. His research bridges theoretical computer vision with practical implementations, making significant contributions to both academic knowledge and real-world applications in healthcare, autonomous systems, and visual recognition technologies.