Papers with Code 아카이브

Few-Shot Transfer Learning for Saliency Prediction

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
4
보존된 평가 기록
5

Saliency prediction aims to predict important locations in a visual scene. It is a per-pixel regression task with predicted values ranging from 0 to 1.

Benefiting from deep learning research and large-scale datasets, saliency prediction has achieved significant success in the past decade. However, it still remains challenging to predict saliency maps on images in new domains that lack sufficient data for data-hungry models.

평가 결과

데이터셋과 평가 조건을 선택해 성능·논문·코드를 비교하세요. 보존된 Papers with Code 기록으로, 최신 순위는 아닙니다.

SALICON->WebpageSaliency - 1-shot

원본 태스크: Saliency Detection / Saliency Prediction / Few-Shot Transfer Learning for Saliency Prediction

평가 기록 2건

SALICON->WebpageSaliency - 5-shot

원본 태스크: Saliency Detection / Saliency Prediction / Few-Shot Transfer Learning for Saliency Prediction

평가 기록 1건

SALICON->WebpageSaliency - EUB

원본 태스크: Saliency Detection / Saliency Prediction / Few-Shot Transfer Learning for Saliency Prediction

평가 기록 1건

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.