Sense-X/Co-DETR

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1357 stars · 180 forks observed · 2026-08-28

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

Co-DETR is a PyTorch implementation of DETRs with Collaborative Hybrid Assignments Training, an ICCV 2023 object detection and instance segmentation framework. It provides pretrained models and configs that achieve state-of-the-art results on COCO and LVIS benchmarks.

Use cases

• train state-of-the-art object detection models on COCO
• run instance segmentation with DETR-based transformers
• fine-tune a ViT-L detector on custom datasets
• get pretrained detection checkpoints from Hugging Face
• benchmark DETR variants on LVIS
• use a strong vision backbone for multimodal models

When to choose

• you need top-accuracy object detection or instance segmentation with transformer detectors
• you want reproducible configs and pretrained weights for COCO/LVIS research
• you need a strong vision encoder for downstream multimodal tasks

When to avoid

• you need lightweight real-time detection on edge devices
• you want a plug-and-play production API rather than a research codebase
• you work outside the PyTorch/MMDetection ecosystem

Facets

library · maturity stable

machine-learning deep-learning computer-vision image-processing computer-vision deep-learning machine-learning artificial-intelligence python object-detection detr instance-segmentation transformer iccv-2023 coco lvis research linux gpu

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markdown · JSON · MCP: product_card(name="Sense-X/Co-DETR")