태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
When a camera is pointed at a strong light source, the resulting photograph may contain lens flare artifacts. Flares appear in a wide variety of patterns (halos, streaks, color bleeding, haze, etc.) and this diversity in appearance makes flare removal challenging.
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
Flare7K, the first nighttime flare removal dataset, which is generated based on the observation and statistic of real-world nighttime lens flares. It offers 5,000 scattering flare images and 2,000 reflective flare images, consisting of 25 types of scattering flares and 10 types of reflective flares. The 7,000 flare patterns can be randomly added to the flare-free images, forming the flare-corrupted and flare-free image pairs.
The FlareReal600 is a nighttime flare removal dataset, which contains 650 real-captured images pairs and 500 flare images. The training set contains 600 images pairs and 500 flare images and the validation set contains 50 image pairs. Images pairs within the dataset are captured from various place (e.g., street, park, indoor) and under incorrect & correct exposure settings. Each flare-corrupted image contains various light sources. Flare images are captured from a dark room with multiple-color light sources.
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.