microsoft/conditional-detr-resnet-50
object-detection model by microsoft
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Model card & documentation
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Conditional DEtection TRansformer (DETR) model trained end-to-end on COCO 2017 object detection (118k annotated images). It was introduced in the paper Conditional DETR for Fast Training Convergence by Meng et al. and first released in this repository. The recently-developed DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings for localizing the four extremities and predicting the box, which increases the need for high-quality content embeddings and thus the training difficulty. Our approach, named conditional DETR, learns a conditional spatial query from the decoder embedding for decoder multi-head cross-attention. The benefit is that through the conditional spatial query, each cross-attention head is able to attend to a…
Read the full model card ↗ · Preview checked 2026-10-28T04:00:50.806Z
Inside the original model card — Document outline
- Conditional DETR model with ResNet-50 backbone
- Model description
- Intended uses & limitations
- How to use
- Training data
- BibTeX entry and citation info
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Model overview
microsoft/conditional-detr-resnet-50 is a object-detection model repository published by microsoft on Hugging Face. The source reports the transformers library.
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Model facts
- Task
- object-detection
- Library
- transformers
- Recent downloads (30 days)
- 9,460
- Cumulative likes
- 23
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 43,524,641
- Architecture
- ConditionalDETRForObjectDetection
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2022-09-09T06:11:40.000Z
- Last modified
- 2024-05-08T07:48:26.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:34.007Z. Daily imports are snapshots, not real-time monitoring.
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