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ADN for object detection [PDF]
IET Computer Vision, 2020 Owing to large‐scale diversity and location uncertainty in object detection, how to enrich semantic information has become an important issue that attracts a lot of concern.
Jinding Wang, Haifeng Hu, Xinlong Lu
doaj +3 more sources
DOTA: A Large-scale Dataset for Object Detection in Aerial Images [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 Object detection is an important and challenging problem in computer vision. Although the past decade has witnessed major advances in object detection in natural scenes, such successes have been slow to aerial imagery, not only because of the huge ...
Bai, Xiang +8 more
core +4 more sources
Toward Versatile Small Object Detection with Temporal-YOLOv8 [PDF]
SensorsDeep learning has become the preferred method for automated object detection, but the accurate detection of small objects remains a challenge due to the lack of distinctive appearance features.
Martin C. van Leeuwen +4 more
doaj +2 more sources
RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements [PDF]
SensorsRoad object detection technology is a key technology to achieve intelligent assisted driving. The complexity and variability of real-world road environments make the detection of densely occluded objects more challenging in autonomous driving scenarios ...
Tianyu Li +8 more
doaj +2 more sources
Concealed Object Detection [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 17 pages, 27 figures, Code: https://github.com/GewelsJI/SINet ...
Deng-Ping Fan +3 more
openaire +4 more sources
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection [PDF]
European Conference on Computer Vision, 2023 In this paper, we present an open-set object detector, called Grounding DINO, by marrying Transformer-based detector DINO with grounded pre-training, which can detect arbitrary objects with human inputs such as category names or referring expressions ...
Shilong Liu +10 more
semanticscholar +1 more source
YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications [PDF]
arXiv.org, 2022 For years, the YOLO series has been the de facto industry-level standard for efficient object detection. The YOLO community has prospered overwhelmingly to enrich its use in a multitude of hardware platforms and abundant scenarios.
Chuyin Li +17 more
semanticscholar +1 more source
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection [PDF]
International Conference on Learning Representations, 2022 We present DINO (\textbf{D}ETR with \textbf{I}mproved de\textbf{N}oising anch\textbf{O}r boxes), a state-of-the-art end-to-end object detector. % in this paper.
Hao Zhang +7 more
semanticscholar +1 more source
Focal Loss for Dense Object Detection [PDF]
IEEE International Conference on Computer Vision, 2017 The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations.
Tsung-Yi Lin +4 more
semanticscholar +2 more sources
Multiview-Learning-Based Generic Palmprint Recognition: A Literature Review
Mathematics, 2023 Palmprint recognition has been widely applied to security authentication due to its rich characteristics, i.e., local direction, wrinkle, and texture.
Shuping Zhao, Lunke Fei, Jie Wen
doaj +1 more source