# fundamentalvision/deformable-detr

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3,895 stars · 612 forks · Python · apache-2.0

## Links

- GitHub: https://github.com/fundamentalvision/Deformable-DETR
- awesome-repositories: https://awesome-repositories.com/repository/fundamentalvision-deformable-detr.md

## Description

Deformable-DETR is an object detection system for computer vision that uses a transformer-based encoder-decoder architecture. It identifies and locates objects within images by representing potential targets as a set of learnable queries.

The project employs sampling-based attention to restrict attention to a small set of points around a reference, reducing computational complexity and speeding up convergence. It further utilizes multi-scale feature fusion to detect objects of varying sizes within a single frame.

The system includes capabilities for training models across multiple GPU clusters using distributed data parallelism and evaluating detection precision against standard benchmark datasets.

## Tags

### Artificial Intelligence & ML

- [Deformable Attention](https://awesome-repositories.com/f/artificial-intelligence-ml/attention-mechanisms/deformable-attention.md) — Implements deformable attention by sampling a small set of points around a reference to reduce complexity.
- [Object Detection](https://awesome-repositories.com/f/artificial-intelligence-ml/computer-vision-systems/computer-vision/object-detection-tracking/object-detection.md) — Identifies and locates specific objects within images using bounding boxes and classification. ([source](https://cdn.jsdelivr.net/gh/fundamentalvision/deformable-detr@main/README.md))
- [Detection Model Training](https://awesome-repositories.com/f/artificial-intelligence-ml/custom-model-training/detection-model-training.md) — Trains deep learning models to identify and locate multiple objects within images using transformer architectures.
- [Multi-Scale Feature Pyramids](https://awesome-repositories.com/f/artificial-intelligence-ml/inference-scaling/resolution-scaling/hierarchical-feature-pyramids/multi-scale-feature-pyramids.md) — Uses multi-scale feature pyramids to detect objects of varying sizes within a single image frame.
- [Transformer-Based Architectures](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/architectures/computer-vision-segmentation-models/object-detection-models/transformer-based-architectures.md) — Utilizes a transformer-based encoder-decoder architecture to generate object queries for set prediction.
- [Object Query Mechanisms](https://awesome-repositories.com/f/artificial-intelligence-ml/object-query-mechanisms.md) — Employs learnable object queries that interact via attention to predict bounding boxes and object classes.
- [Data-Parallel Training](https://awesome-repositories.com/f/artificial-intelligence-ml/distributed-training-frameworks/data-parallel-training.md) — Provides data-parallel training to synchronize gradients across multiple GPU nodes for faster convergence.
- [Hungarian Matching Losses](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/architectures/neural-network-components/loss-functions/perceptual-loss/content-loss-calculators/focal-loss-calculators/detection-loss-calculators/hungarian-matching-losses.md) — Implements bipartite matching losses to assign predicted boxes to ground truth objects without hand-crafted anchors.
- [GPU Training Accelerators](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/machine-learning-training/distributed-and-accelerated-compute/training-acceleration-tools/gpu-training-accelerators.md) — Accelerates training speed by parallelizing workloads across multiple GPU clusters.
- [Distributed Training](https://awesome-repositories.com/f/artificial-intelligence-ml/machine-learning/infrastructure/machine-learning-training/distributed-training.md) — Scales the training of the object detection model across multiple compute nodes. ([source](https://cdn.jsdelivr.net/gh/fundamentalvision/deformable-detr@main/README.md))

### Part of an Awesome List

- [Object Detection and Segmentation](https://awesome-repositories.com/f/awesome-lists/ai/object-detection-and-segmentation.md) — Deformable transformers for end-to-end object detection.