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Causal Invariant Representation Learning Based on Style Intervention Identity Regularization for Remote Sensing Image
An intelligent understanding model of a remote sensing image will present different visual representations of the same object in the remote sensing image, under the interference of offset factors, such as weather and season. This variability adversely affects the generalization ability of the model; therefore, an open challenge is how to learn invariant features. These features can maintain the mo...Show More
GLINet: Global-Local Interacting Network for Object Detection Under Inclement Weather Conditions
2024 IEEE 7th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC)
Year: 2024 | Conference Paper |
Recently, deep learning-based object detection methods have achieved promising success in normal scenarios. However, the performance of such methods often fails to locate objects from the degraded images captured under inclement weather conditions. The existing methods mostly utilize image enhancement techniques or domain adaptation methods, which focus on local improvement and ignore global infor...Show More
WB-DETR: Transformer-Based Detector without Backbone
Fanfan Liu;Haoran Wei;Wenzhe Zhao;Guozhen Li;Jingquan Peng;Zihao Li
2021 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2021 | Conference Paper |
Cited by: Papers (21)
Transformer-based detector is a new paradigm in object detection, which aims to achieve pretty-well performance while eliminates the priori knowledge driven components, e.g., anchors, proposals and the NMS. DETR, the state-of-the-art model among them, is composed of three sub-modules, i.e., a CNN-based backbone and paired transformer encoder-decoder. The CNN is applied to extract local features an...Show More
VisDrone-DET2021: The Vision Meets Drone Object detection Challenge Results
Yaru Cao;Zhijian He;Lujia Wang;Wenguan Wang;Yixuan Yuan;Dingwen Zhang;Jinglin Zhang;Pengfei Zhu;Luc Van Gool;Junwei Han;Steven Hoi;Qinghua Hu;Ming Liu;Chong Cheng;Fanfan Liu;Guojin Cao;Guozhen Li;Hongkai Wang;Jianye He;Junfeng Wan;Qi Wan;Qi Zhao;Shuchang Lyu;Wenzhe Zhao;Xiaoqiang Lu;Xingkui Zhu;Yingjie Liu;Yixuan Lv;Yujing Ma;Yuting Yang;Zhe Wang;Zhenyu Xu;Zhipeng Luo;Zhimin Zhang;Zhiguang Zhang;Zihao Li;Zixiao Zhang
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
Year: 2021 | Conference Paper |
Cited by: Papers (130)
Object detection on the drone faces a great diversity of challenges such as small object inference, background clutter and wide viewpoint. In contrast to traditional detection problem in computer vision, object detection in bird-like angle can not be transplanted directly from common-in-use methods due to special object texture in sky‘s view. However, due to the lack of a comprehensive data set, t...Show More
VisDrone-DET2021: The Vision Meets Drone Object detection Challenge Results
Yaru Cao;Zhijian He;Lujia Wang;Wenguan Wang;Yixuan Yuan;Dingwen Zhang;Jinglin Zhang;Pengfei Zhu;Luc Van Gool;Junwei Han;Steven Hoi;Qinghua Hu;Ming Liu;Chong Cheng;Fanfan Liu;Guojin Cao;Guozhen Li;Hongkai Wang;Jianye He;Junfeng Wan;Qi Wan;Qi Zhao;Shuchang Lyu;Wenzhe Zhao;Xiaoqiang Lu;Xingkui Zhu;Yingjie Liu;Yixuan Lv;Yujing Ma;Yuting Yang;Zhe Wang;Zhenyu Xu;Zhipeng Luo;Zhimin Zhang;Zhiguang Zhang;Zihao Li;Zixiao Zhang
Year: 2021 | Conference Paper |
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