OPA: Object Placement Assessment Dataset

• URL: http://arxiv.org/abs/2107.01889v1
• Date: Mon, 5 Jul 2021 09:23:53 GMT
• Title: OPA: Object Placement Assessment Dataset
• Authors: Liu Liu, Bo Zhang, Jiangtong Li, Li Niu, Qingyang Liu, Liqing Zhang
• Abstract summary: Image composition aims to generate realistic composite image by inserting an object from one image into another background image. In this paper, we focus on object placement assessment task, which verifies whether a composite image is plausible in terms of the object placement.
• Score: 20.791187775546625
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Image composition aims to generate realistic composite image by inserting an object from one image into another background image, where the placement (e.g., location, size, occlusion) of inserted object may be unreasonable, which would significantly degrade the quality of the composite image. Although some works attempted to learn object placement to create realistic composite images, they did not focus on assessing the plausibility of object placement. In this paper, we focus on object placement assessment task, which verifies whether a composite image is plausible in terms of the object placement. To accomplish this task, we construct the first Object Placement Assessment (OPA) dataset consisting of composite images and their rationality labels. Dataset is available at https://github.com/bcmi/Object-Placement-Assessment-Dataset-OPA.

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