{"slug": "is-there-any-full-vision-transformer-model-for-object-detection", "title": "Is there any full Vision transformer model for object detection?", "summary": "Multiple full Vision Transformer (ViT) object detection models exist, including LW-DETR, RF-DETR, YOLOS, ViTDet, and WB-DETR, each differing in architectural purity and usability. The choice depends on whether the user prioritizes a plain ViT backbone with a DETR-style decoder, practical performance, or minimal modifications to vanilla ViT.", "body_md": "Probably, yes:\n\nIf by “full Vision Transformer” you mean **an object detector whose main visual backbone is a ViT rather than a CNN**, there are several examples now.\n\nFor the specific shape you mentioned — **something like a plain ViT backbone + a DETR-style head/decoder** — I would start with ** LW-DETR**. Hugging Face describes its architecture as a\n\nIf you want a newer, practical detector built around a pretrained ViT backbone, ** RF-DETR** is also worth looking at. It uses a\n\nAnd if what you mean is closer to **“vanilla ViT itself turned into an object detector”**, then ** YOLOS** is probably the cleanest reference point. It modifies ViT only minimally and adds detection tokens/heads rather than attaching a conventional DETR encoder-decoder stack.\n\nSo, roughly:\n\n| What you are looking for | Candidate | Transformers usability |\n|---|---|---|\n| plain ViT + DETR-style decoder |\n|\n\n`pipeline`\n\n/ `AutoModelForObjectDetection`\n\n`pipeline`\n\n/ `AutoModelForObjectDetection`\n\nThe only thing I would be careful about is the word **“entirely”**, because there are a few different meanings hiding inside it.\n\nIf I were choosing where to start:\n\n```\nWant the closest thing to \"plain ViT backbone + DETR head\"?\n    → LW-DETR\n\nWant a newer practical ViT-based detector with good current HF support?\n    → RF-DETR\n\nWant the cleanest vanilla-ViT-as-detector reference?\n    → YOLOS\n\nWant to build a ViT backbone + strong DETR-family detector yourself?\n    → ViTDet + DINO/detrex\n\nWant specifically \"no CNN backbone\" as a research constraint?\n    → WB-DETR\n\nWant literally zero Conv2d / convolution operations?\n    → treat that as a separate requirement and audit the exact model implementation\n```\n\nSo the answer is definitely not “there is no full-ViT object detector”; rather, there are several families already. The main choice is **what you mean by “full”** and whether your priority is architectural purity, a DETR-like component boundary, current Transformers usability, or practical detection performance.", "url": "https://wpnews.pro/news/is-there-any-full-vision-transformer-model-for-object-detection", "canonical_source": "https://discuss.huggingface.co/t/is-there-any-full-vision-transformer-model-for-object-detection/179750#post_2", "published_at": "2026-09-02 10:01:56+00:00", "updated_at": "2026-09-02 10:25:21.020885+00:00", "lang": "en", "topics": ["artificial-intelligence", "machine-learning", "computer-vision", "ai-research"], "entities": ["LW-DETR", "RF-DETR", "YOLOS", "ViTDet", "WB-DETR", "Hugging Face", "DETR"], "alternates": {"html": "https://wpnews.pro/news/is-there-any-full-vision-transformer-model-for-object-detection", "markdown": "https://wpnews.pro/news/is-there-any-full-vision-transformer-model-for-object-detection.md", "text": "https://wpnews.pro/news/is-there-any-full-vision-transformer-model-for-object-detection.txt", "jsonld": "https://wpnews.pro/news/is-there-any-full-vision-transformer-model-for-object-detection.jsonld"}}