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Fewer is more: efficient object detection in large aerial images
Current mainstream object detection methods for large aerial images usually divide large images into patches and then exhaustively detect the objects...
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Universal Object Detection with Large Vision Model
Over the past few years, there has been growing interest in develo** a broad, universal, and general-purpose computer vision system. Such systems...
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Robust monocular object pose tracking for large pose shift using 2D tracking
Monocular object pose tracking has been a key technology in autonomous rendezvous of two moving platforms. However, rapid relative motion between...
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SORDI.ai: large-scale synthetic object recognition dataset generation for industries
Smart robots play a crucial role in assisting human workers within manufacturing units (like Industry 4.0) by perceiving and analyzing their...
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Object panorama construction using large-parallax images
Conventional panorama techniques create a wide-angle image by stitching images taken from the same viewpoint. In contrast, the method proposed in...
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Video Object Segmentation Tasks, Datasets, and Methods
This book provides a thorough overview of recent progress in video object segmentation, providing researchers and industrial practitioners with...
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Object search by a concept-conditioned object detector
Object detectors are used for searching all objects belonging to a pre-defined set of categories contained in a given picture. However, users are...
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Object coverage criteria for supporting object-oriented testing
Code coverage criteria are widely used in object-oriented (OO) domains as test quality indicators. However, these criteria are based on the...
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Cross-domain object detection by local to global object-aware feature alignment
Cross-domain object detection has attracted more and more attention recently. It reduces the gap between the two domains, where the source domain is...
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Multi-object behaviour recognition based on object detection cascaded image classification in classroom scenes
For multi-object behaviour recognition in classroom scenes, crowded objects have heavy occlusion, invisible keypoints, scale variation, which...
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Video Object Tracking Tasks, Datasets, and Methods
This book provides a thorough overview of recent progress in video object tracking, allowing researchers and industrial practitioners to gain a...
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Towards robustness and generalization of point cloud representation: A geometry coding method and a large-scale object-level dataset
Robustness and generalization are two challenging problems for learning point cloud representation. To tackle these problems, we first design a novel...
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Ownership of abandoned object detection by integrating carried object recognition and context sensing
Abandoned baggage poses a potential threat to public safety, which needs to be monitored to avoid catastrophic effects. Identifying left baggage, the...
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Geometric relation-based feature aggregation for 3D small object detection
Point cloud-based 3D small object detection is crucial for autonomous driving and smart ships. The current 3D object detection mainly relies on...
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Regional filtering distillation for object detection
Knowledge distillation is a common and effective method in model compression, which trains a compact student model to mimic the capability of a large...
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A survey of model compression strategies for object detection
Deep neural networks (DNNs) have achieved great success in many object detection tasks. However, such DNNS-based large object detection models are...
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I-YOLO: a novel single-stage framework for small object detection
Small object detection is a challenging task in computer vision. We claim that the huge performance gap between the small object detectors and normal...
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Gradient optimization for object detection in learning with noisy labels
Deep neural networks have made significant progress benefiting large-scale correctly human-labeled datasets. However, large-scale human-labeled...
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Focal segmentation for robust 6D object pose estimation
In the field of augmented reality, 6D pose estimation of rigid objects poses limitations and challenges. Most of the previous 6D pose estimation...
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Online object-level SLAM with dual bundle adjustment
Object-level landmarks enable the SLAM system to construct robust object-keyframe constraints of bundle adjustment and improve the pose estimation...
