DeSRA
DeSRA provides methods to identify and eliminate artifacts from GAN-inferred super-resolution models using minimal image data for fine-tuning. It facilitates real-world super-resolution application by releasing datasets, detection codes, and models such as Real-ESRGAN, LDL, and SwinIR. Supported by SegFormer and Python, it evaluates artifact detection with IOU, precision, and recall metrics. Access resources including pre-trained models and download options.
