Deep-Hough-Transform-Line-Priors
Line Detector
This implementation introduces line priors into a deep learning-based line detection system to improve efficiency and accuracy.
Official implementation for Deep-Hough-Transform-Line-Priors (ECCV 2020)
163 stars
7 watching
31 forks
Language: Python
last commit: 3 months ago Related projects:
Repository | Description | Stars |
---|---|---|
| A deep learning-based approach to semantic line detection | 345 |
| An implementation of line segment detection using convolutional neural networks and a coupled region coloring problem | 297 |
| A deep learning framework for detecting and describing lines in images, particularly robust to occlusion | 549 |
| Provides an implementation of a neural network for detecting lines in images and videos | 156 |
| Develops a deep learning model for large-scale object detection that leverages hybrid knowledge and routing mechanisms. | 105 |
| A software framework for detecting and refining line segments in images using deep learning techniques | 497 |
| Deep learning models for semantic segmentation of images | 101 |
| This project presents a PyTorch implementation of a deep learning algorithm for detecting line segments in images. | 172 |
| This code implements a neural network architecture designed to perform semantic segmentation in computer vision tasks. | 920 |
| Develops efficient and real-time line segment detection software for resource-constrained environments. | 543 |
| Developing and evaluating deep learning models for time series classification with a focus on interpretability and deployability. | 682 |
| A deep learning framework for instance co-segmentation and object colocalization | 137 |
| This implementation enables unsupervised translation between two domains with drastic visual discrepancies using a Generative Prior-guided approach. | 193 |
| Develops a deep learning-based contour detection system with a focus on accuracy and performance. | 94 |
| This project proposes a solution to predict salient areas in images using convolutional neural networks. | 186 |