hasanirtiza/PedesFormer-Transformer-Networks-For-Pedestrian-Detection

Transformer Networks for Pedestrian Detection

38
/ 100
Emerging

This tool helps researchers in computer vision advance the state-of-the-art in detecting pedestrians in images and video. It takes in existing pedestrian detection datasets, like those used in autonomous driving, and provides trained models and benchmarks for evaluating new transformer-based detection methods. It's intended for researchers focused on improving how artificial intelligence identifies people in visual data.

No commits in the last 6 months.

Use this if you are a computer vision researcher working on improving pedestrian detection algorithms, particularly with transformer networks, and need a base for benchmarking.

Not ideal if you are a practitioner looking for a ready-to-deploy solution for a specific application like surveillance or self-driving, rather than a research tool.

pedestrian-detection computer-vision-research autonomous-driving-research deep-learning-benchmarking transformer-models
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

43

Forks

7

Language

Python

License

Apache-2.0

Last pushed

May 29, 2022

Commits (30d)

0

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