Image Processing
Image processing focuses on manipulating digital images to enhance quality, extract information, or perform specific tasks. Current research emphasizes deep learning approaches, particularly convolutional neural networks (CNNs) and transformers, for applications ranging from medical image analysis (e.g., detecting diabetic retinopathy) and geospatial image analysis to object detection and style transfer. These advancements are improving the efficiency and accuracy of various fields, from healthcare diagnostics and infrastructure monitoring to resource management and scientific discovery.
Papers
LossAgent: Towards Any Optimization Objectives for Image Processing with LLM Agents
Bingchen Li, Xin Li, Yiting Lu, Zhibo Chen
EditScout: Locating Forged Regions from Diffusion-based Edited Images with Multimodal LLM
Quang Nguyen, Truong Vu, Trong-Tung Nguyen, Yuxin Wen, Preston K Robinette, Taylor T Johnson, Tom Goldstein, Anh Tran, Khoi Nguyen
MagicQuill: An Intelligent Interactive Image Editing System
Zichen Liu, Yue Yu, Hao Ouyang, Qiuyu Wang, Ka Leong Cheng, Wen Wang, Zhiheng Liu, Qifeng Chen, Yujun Shen
Image Processing for Motion Magnification
Nadaniela Egidi, Josephin Giacomini, Paolo Leonesi, Pierluigi Maponi, Federico Mearelli, Edin Trebovic