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Found 8 papers, 4 papers with code
Leveraging Model Fusion for Improved License Plate Recognition
License Plate Recognition (LPR) plays a critical role in various applications, such as toll collection, parking management, and traffic law enforcement.
Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognition
This work draws attention to the large fraction of near-duplicates in the training and test sets of datasets widely adopted in License Plate Recognition (LPR) research.
Global Semantic Descriptors for Zero-Shot Action Recognition
This work introduces a new ZSAR method based on the relationships of actions-objects and actions-descriptive sentences.
A First Look at Dataset Bias in License Plate Recognition
We performed experiments on eight datasets, four collected in Brazil and four in mainland China, and observed that each dataset has a unique, identifiable "signature" since a lightweight classification model predicts the source dataset of a license plate (LP) image with more than 95% accuracy.
On the Cross-dataset Generalization in License Plate Recognition
Automatic License Plate Recognition (ALPR) systems have shown remarkable performance on license plates (LPs) from multiple regions due to advances in deep learning and the increasing availability of datasets.
Tell me what you see: A zero-shot action recognition method based on natural language descriptions
To the best of our knowledge, this is the first work to represent both videos and labels with descriptive sentences.
Dense Video Captioning Using Unsupervised Semantic Information
We introduce a method to learn unsupervised semantic visual information based on the premise that complex events (e. g., minutes) can be decomposed into simpler events (e. g., a few seconds), and that these simple events are shared across several complex events.
Zero-Shot Action Recognition in Videos: A Survey
Zero-Shot Action Recognition has attracted attention in the last years and many approaches have been proposed for recognition of objects, events and actions in images and videos.
Action Recognition In Still Images
Action Recognition In Videos
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