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
On Feature Decorrelation in Cloth-Changing Person Re-identification
Hongjun Wang, Jiyuan Chen, Renhe Jiang, Xuan Song, Yinqiang Zheng
Systematic Literature Review of Vision-Based Approaches to Outdoor Livestock Monitoring with Lessons from Wildlife Studies
Stacey D. Scott, Zayn J. Abbas, Feerass Ellid, Eli-Henry Dykhne, Muhammad Muhaiminul Islam, Weam Ayad, Kristina Kacmorova, Dan Tulpan, Minglun Gong
PRFusion: Toward Effective and Robust Multi-Modal Place Recognition with Image and Point Cloud Fusion
Sijie Wang, Qiyu Kang, Rui She, Kai Zhao, Yang Song, Wee Peng Tay
Machine learning approaches for automatic defect detection in photovoltaic systems
Swayam Rajat Mohanty, Moin Uddin Maruf, Vaibhav Singh, Zeeshan Ahmad
Mind the Prompt: A Novel Benchmark for Prompt-based Class-Agnostic Counting
Luca Ciampi, Nicola Messina, Matteo Pierucci, Giuseppe Amato, Marco Avvenuti, Fabrizio Falchi
A preliminary study on continual learning in computer vision using Kolmogorov-Arnold Networks
Alessandro Cacciatore, Valerio Morelli, Federica Paganica, Emanuele Frontoni, Lucia Migliorelli, Daniele Berardini
Formula-Supervised Visual-Geometric Pre-training
Ryosuke Yamada, Kensho Hara, Hirokatsu Kataoka, Koshi Makihara, Nakamasa Inoue, Rio Yokota, Yutaka Satoh
A Deep Learning Approach for Pixel-level Material Classification via Hyperspectral Imaging
Savvas Sifnaios, George Arvanitakis, Fotios K. Konstantinidis, Georgios Tsimiklis, Angelos Amditis, Panayiotis Frangos
Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go?
Jae Hee Lee, Georgii Mikriukov, Gesina Schwalbe, Stefan Wermter, Diedrich Wolter
Enhancing Fruit and Vegetable Detection in Unconstrained Environment with a Novel Dataset
Sandeep Khanna, Chiranjoy Chattopadhyay, Suman Kundu