Chang Chen, Zhiwei Xiong, Xiaoming Liu, Feng Wu. Camera Trace Erasing. In CVPR 2020.
Anaconda>=5.2.0 (Python 3.6)
PyTorch>=1.0.1
Matlab R2018b (and above)
Download *.zip files, and unzip them to "datas" and "results", respectively
http://pan.bitahub.com/index.php?mod=shares&
sid=eTJ2bFFQR3BzTm5FTGxONHJ3WXZzTTlobjItSTFzYl9vTmVySlE
├─datas
│ ├─KCMI-550.zip
│ │ ├─KCMI-550 // Images for testing
│ │ ├─KCMI-550-Val // List of images
│ ├─VISION-1500.zip
│ │ ├──VISION-1500 // Images for testing
│ ├─KCMI+.zip
│ │ ├─KCMI+ // Images for training
├─libs
│ ├─CameraFingerprint // Library for verification
│ ├─KMCUDA // Source code for building
│ ├─libKMCUDA.so // Library for CUDA-based K-means
├─models // Pre-trained models
├─results
│ ├─KCMI-550-Ours.zip
│ │ ├──KCMI-550-Ours // Generated results
│ │ ├──KCMI-550-Crop // Centrally cropped images
│ │ ├──KCMI-550-Crop-Ours // Generated results
│ │ ├──KCMI-Fingerprint // Fingerprint of training data
│ ├─VISION-1500-Ours.zip
│ │ ├──VISION-1500-Ours // Generated results
│ │ ├──VISION-1500-Ours-ResNet // Extracted features of results
│ │ ├──VISION-1500-Ours-DenseNet // Extracted features of results
├─inference_classification.py // Classification task
├─inference_clustering.py // Clustering task
├─inference_verification.m // Verification task
├─inference_siamte.py // Method for camera trace erasing
├─inference_feature.py // Feature extraction for clustering
├─measure_l1.py // L1 distance
├─measure_niqe.m // Naturalness Image Quality Evaluator