Papers with Code 아카이브

Image Shadow Removal

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
1
보존된 평가 기록
1

Merge with the Shadow Removal

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

INS Dataset

A significant challenge in removing shadows from indoor scenes is obtaining shadow-free images. To overcome this challenge, we propose a novel rendering pipeline for generating shadowed and shadow-free images under direct and indirect illumination, and create a comprehensive synthetic dataset that contains over 30,000 image pairs, covering various object types and lighting conditions. We implemented a direct/indirect shadow and shadow-free rendering pipeline using Blender Cycles engine, with the help of Open Shading Language (OSL). The resulting collection of shadow and shadow-free images is referred to as the “INS dataset”. The dataset includes 30,000 training and 2,000 testing images, all with a resolution of 512 × 512. The training and testing images are generated from distinct scenes with different objects and materials.

SD7K

SD7K is the only large-scale high-resolution dataset that satisfies all important data features about document shadow currently, which covers a large number of document shadow images. Mean resolution is $2462 \times 3699$

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