Region Proposal
143 papers with code • 1 benchmarks • 5 datasets
Libraries
Use these libraries to find Region Proposal models and implementationsMost implemented papers
Focal Loss for Dense Object Detection
Our novel Focal Loss focuses training on a sparse set of hard examples and prevents the vast number of easy negatives from overwhelming the detector during training.
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
In this work, we introduce a Region Proposal Network (RPN) that shares full-image convolutional features with the detection network, thus enabling nearly cost-free region proposals.
Frustum PointNets for 3D Object Detection from RGB-D Data
In this work, we study 3D object detection from RGB-D data in both indoor and outdoor scenes.
VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Accurate detection of objects in 3D point clouds is a central problem in many applications, such as autonomous navigation, housekeeping robots, and augmented/virtual reality.
Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisy-or Network
The model consists of two modules.
Complex-YOLO: Real-time 3D Object Detection on Point Clouds
We introduce Complex-YOLO, a state of the art real-time 3D object detection network on point clouds only.
Domain Adaptive Faster R-CNN for Object Detection in the Wild
The results demonstrate the effectiveness of our proposed approach for robust object detection in various domain shift scenarios.
DeepText: A Unified Framework for Text Proposal Generation and Text Detection in Natural Images
In this paper, we develop a novel unified framework called DeepText for text region proposal generation and text detection in natural images via a fully convolutional neural network (CNN).
High Performance Visual Tracking With Siamese Region Proposal Network
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection
In this paper, we take a slightly different viewpoint -- we find that precise positioning of raw points is not essential for high performance 3D object detection and that the coarse voxel granularity can also offer sufficient detection accuracy.