GOATmessi8/RFBNet

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1419 stars · 347 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

PyTorch implementation of RFBNet, a Receptive Field Block Net object detector presented at ECCV 2018. It enhances SSD-style detectors with an RFB module for fast, accurate object detection on VOC and COCO, including lightweight MobileNet variants.

Use cases

• train an object detection model in pytorch
• run fast real-time object detection on images
• reproduce ECCV 2018 RFBNet results on COCO and VOC
• build a lightweight mobile-friendly detector with mobilenet backbone
• compare SSD and RFBNet detection accuracy and speed
• fine-tune a pretrained object detector on custom datasets

When to choose

• you need a fast SSD-style detector with strong accuracy benchmarks
• you want a research reference implementation of the RFB paper
• you need a lightweight mobilenet-based detector with few parameters

When to avoid

• you need a modern, actively maintained detection framework
• you want built-in ONNX/TensorRT deployment support
• you need the latest state-of-the-art detectors like YOLOX or transformers

Facets

library · maturity maintenance

machine-learning computer-vision deep-learning computer-vision deep-learning machine-learning python object-detection pytorch ssd mobilenet eccv-2018 research-code gpu linux

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