Papers with Code 아카이브

Dichotomous Image Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
6
보존된 평가 기록
113

Currently, existing image segmentation tasks mainly focus on segmenting objects with specific characteristics, e.g., salient, camouflaged, meticulous, or specific categories. Most of them have the same input/output formats, and barely use exclusive mechanisms designed for segmenting targets in their models, which means almost all tasks are dataset-dependent. Thus, it is very promising to formulate a category-agnostic DIS task for accurately segmenting objects with different structure complexities, regardless of their characteristics. Compared with semantic segmentation, the proposed DIS task usually focuses on images with single or a few targets, from which getting richer accurate details of each target is more feasible.

평가 결과

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

DIS-VD

원본 태스크: RGB Salient Object Detection / Dichotomous Image Segmentation

평가 기록 24건

DIS-TE1

원본 태스크: RGB Salient Object Detection / Dichotomous Image Segmentation

평가 기록 22건

DIS-TE2

원본 태스크: RGB Salient Object Detection / Dichotomous Image Segmentation

평가 기록 22건

DIS-TE3

원본 태스크: RGB Salient Object Detection / Dichotomous Image Segmentation

평가 기록 22건

DIS-TE4

원본 태스크: RGB Salient Object Detection / Dichotomous Image Segmentation

평가 기록 22건

STARE

원본 태스크: RGB Salient Object Detection / Dichotomous Image Segmentation

평가 기록 1건

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