Knowledge Commons of Institute of Automation,CAS
Improving Visual Grounding With Visual-Linguistic Verification and Iterative Reasoning | |
Li Yang1,2; Yan Xu3; Chunfeng Yuan1; Wei Liu1; Bing Li1; Weiming Hu1,2,4 | |
2022-06 | |
会议名称 | IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 |
会议日期 | 2022-6 |
会议地点 | New Orleans, Louisiana |
出版者 | Institute of Electrical and Electronics Engineers (IEEE) |
摘要 | Visual grounding is a task to locate the target indicated by a natural language expression. Existing methods extend the generic object detection framework to this problem. They base the visual grounding on the features from pre-generated proposals or anchors, and fuse these features with the text embeddings to locate the target mentioned by the text. However, modeling the visual features from these predefined locations may fail to fully exploit the visual context and attribute information in the text query, which limits their performance. In this paper, we propose a transformer-based framework for accurate visual grounding by establishing text-conditioned discriminative features and performing multi-stage cross-modal reasoning. Specifically, we develop a visual-linguistic verification module to focus the visual features on regions relevant to the textual descriptions while suppressing the unrelated areas. A language-guided feature encoder is also devised to aggregate the visual contexts of the target object to improve the object's distinctiveness. To retrieve the target from the encoded visual features, we further propose a multi-stage cross-modal decoder to iteratively speculate on the correlations between the image and text for accurate target localization. Extensive experiments on five widely used datasets validate the efficacy of our proposed components and demonstrate state-of-the-art performance. |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
国重实验室规划方向分类 | 多模态协同认知 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/52140 |
专题 | 多模态人工智能系统全国重点实验室_视频内容安全 |
通讯作者 | Chunfeng Yuan |
作者单位 | 1.NLPR, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences 3.The Chinese University of Hong Kong 4.CAS Center for Excellence in Brain Science and Intelligence Technology |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Li Yang,Yan Xu,Chunfeng Yuan,et al. Improving Visual Grounding With Visual-Linguistic Verification and Iterative Reasoning[C]:Institute of Electrical and Electronics Engineers (IEEE),2022. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Yang_Improving_Visua(2060KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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