Video Object Detection with Locally-Weighted Deformable Neighbors | |
Jiang, Zhengkai2,3; Gao, Peng4; Guo, Chaoxu2,3; Zhang, Qian1; Xiang, Shiming2,3; Pan, Chunhong2,3 | |
2019-07 | |
会议日期 | 2019-1 |
会议地点 | 美国夏威夷 |
关键词 | Video Object Detection Feature Propagation and Aggregation |
英文摘要 | Deep convolutional neural networks have achieved great success on various image recognition tasks. However, it is nontrivial to transfer the existing networks to video due to the fact that most of them are developed for static image. Frame-byframe processing is suboptimal because temporal information that is vital for video understanding is totally abandoned. Furthermore, frame-by-frame processing is slow and inefficient, which can hinder the practical usage. In this paper, we propose LWDN (Locally-Weighted Deformable Neighbors) for video object detection without utilizing time-consuming optical flow extraction networks. LWDN can latently align the high-level features between keyframes and keyframes or nonkeyframes. Inspired by (Zhu et al. 2017a) and (Hetang et al. 2017) who propose to aggregate features between keyframes and keyframes, we adopt brain-inspired memory mechanism to propagate and update the memory feature from keyframes to keyframes. We call this process Memory-Guided Propagation. With such a memory mechanism, the discriminative ability of features in keyframes and non-keyframes are both enhanced, which helps to improve the detection accuracy. Extensive experiments on VID dataset demonstrate that our method achieves superior performance in a speed and accuracy trade-off, ie, 76.3% on the challenging VID dataset while maintaining 20fps in speed on Titan X GPU. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/39265] |
专题 | 自动化研究所_模式识别国家重点实验室_遥感图像处理团队 |
通讯作者 | Jiang, Zhengkai |
作者单位 | 1.Horizon Robotics 2.National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences 3.School of Artificial Intelligence, University of Chinese Academy of Sciences 4.The Chinese University of Hong Kong |
推荐引用方式 GB/T 7714 | Jiang, Zhengkai,Gao, Peng,Guo, Chaoxu,et al. Video Object Detection with Locally-Weighted Deformable Neighbors[C]. 见:. 美国夏威夷. 2019-1. |
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