태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Image harmonization aims to modify the color of the composited region with respect to the specific background.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
iHarmony4 is a synthesized dataset for Image Harmonization. It contains 4 sub-datasets: HCOCO, HAdobe5k, HFlickr, and Hday2night (based on COCO, Adobe5k, Flickr, day2night datasets respectively), each of which contains synthesized composite images, foreground masks of composite images and corresponding real images. Source: Image_Harmonization_Datasets
A new dataset for portrait harmonization based on the FFHQ. It contains real images, foreground masks, and synthesized composites. Generating composite images has two steps: alpha mask generation and color augmentation. StyleMatte - portrait matting network was used for mask generation. Color augmentations: brightness, contrast, hue, sharpness adjustment. FFHQH includes 60,000 triplets for train, 5000 for validation and 5000 for test. Triplet stands for <real image, mask, composite image>.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.