Traffic Sign Detection
14 papers with code • 3 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Traffic Sign Detection
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CURE-TSR
Latest papers with no code
Traffic Sign Detection With Event Cameras and DCNN
The use of a fusion of the considered representations allows us to obtain a detector with higher accuracy of 89. 9% mAP@0. 5.
Pyramid Transformer for Traffic Sign Detection
The results demonstrate the superiority of the proposed model in the traffic sign detection tasks.
Road images augmentation with synthetic traffic signs using neural networks
Such training data is obtained by embedding synthetic images of signs in the real photos.
Improving Road Signs Detection performance by Combining the Features of Hough Transform and Texture
In this paper, an efficient solution to enhance road signs detection, including Arabic context, performance based on color segmentation, Randomized Hough Transform and the combination of Zernike moments and Haralick features has been made.
Deep Traffic Sign Detection and Recognition Without Target Domain Real Images
The method does not aim at overcoming the training with real data, but to be a compatible alternative when the real data is not available.
Increasing Trustworthiness of Deep Neural Networks via Accuracy Monitoring
In this paper, we address trustworthiness of DNNs by using post-hoc processing to monitor the true inference accuracy on a user's dataset.
DFR-TSD: A Deep Learning Based Framework for Robust Traffic Sign Detection Under Challenging Weather Conditions
However, the SOTA (SOTA) methods have been evaluated on clean and challenge-free datasets and overlooked the performance deterioration associated with different challenging conditions (CCs) that obscure the traffic images captured in the wild.
A Simple Fix for Convolutional Neural Network via Coordinate Embedding
Thus the generalization ability of CNN will be limited since the coordinate information is crucial for a model to learn affine transformations which directly operate on the coordinate of each pixel.
Traffic Signs Detection and Recognition System using Deep Learning
With the rapid development of technology, automobiles have become an essential asset in our day-to-day lives.
Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images
Traffic sign identification using camera images from vehicles plays a critical role in autonomous driving and path planning.
