태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Object proposal generation is a preprocessing technique that has been widely used in current object detection pipelines to guide the search of objects and avoid exhaustive sliding window search across images.
<span style="color:grey; opacity: 0.6">( Image credit: Multiscale Combinatorial Grouping for Image Segmentation and Object Proposal Generation )</span>
출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.
The COCO (Common Objects in Context) dataset is a large-scale object detection, segmentation, and captioning dataset. It is designed to encourage research on a wide variety of object categories and is commonly used for benchmarking computer vision models. It is an essential dataset for researchers and developers working on object detection, segmentation, and pose estimation tasks.
Comic2k is a dataset used for cross-domain object detection which contains 2k comic images with image and instance-level annotations. Image Source: https://naoto0804.github.io/cross_domain_detection/
CocoDoom is a collection of pre-recorded data extracted from Doom gaming sessions along with annotations in the MS Coco format. Source: ResearchDoom and CocoDoom: Learning Computer Vision with Games
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.