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Video Semantic Segmentation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

하위 태스크: 1
평가표: 5
보존된 평가 기록: 26

The goal of video semantic segmentation is to assign a predefined class to each pixel in all frames of a video. This requires the model not only to predict accurate segmentation masks but also to ensure that these masks remain temporally consistent across frames. This task has broad applications in areas such as autonomous driving, medical video analysis, and AR/VR.

평가 결과

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Cityscapes val

원본 태스크: 2D Semantic Segmentation / Scene Parsing / Scene Understanding / Video Semantic Segmentation

평가 기록 9건

CamVid

원본 태스크: 2D Semantic Segmentation / Scene Parsing / Scene Understanding / Video Semantic Segmentation

평가 기록 6건

VSPW

원본 태스크: 2D Semantic Segmentation / Scene Parsing / Scene Understanding / Video Semantic Segmentation

평가 기록 5건

LaRS

원본 태스크: 2D Semantic Segmentation / Scene Parsing / Scene Understanding / Video Semantic Segmentation

평가 기록 3건

Multispectral Video Semantic Segmentation

원본 태스크: 2D Semantic Segmentation / Scene Parsing / Scene Understanding / Video Semantic Segmentation

평가 기록 3건

SoccerNet-v2

원본 태스크: 2D Semantic Segmentation / Scene Parsing / Scene Understanding / Video Semantic Segmentation / Camera shot segmentation

평가 기록 2건

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