Image Feature Extraction Models

Browse AI models for multimodal decomposition and recomposition pipelines: plug any model into your extractors.

781 models available

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Showing 145-168 of 781 models

Image Feature Extraction

paige-ai/Virchow

timm

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Image Feature Extraction

timm/convnext_xxlarge.clip_laion2b_soup

timm

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Image Feature Extraction

marcmarais-ru/seaturtle_reid_mobilenetv2-quadruplet-random-combined_datasets

pytorch

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Image Feature Extraction

timm/convnext_large_mlp.clip_laion2b_ft_soup_320

timm

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Image Feature Extraction

Octopus1/page-vitb-screen

transformers

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Image Feature Extraction

Octopus1/page-vithplus

transformers

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Image Feature Extraction

facebook/hiera-tiny-224-hf

transformers

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Image Feature Extraction

py-feat/img2pose

py-feat

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Image Feature Extraction

birder-project/vit_reg4_so150m_p14_ls_dino-v2-bio

birder

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Image Feature Extraction

Octopus1/page-vitb

transformers

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Image Feature Extraction

allenai/OlmoEarth-v1_2-Nano

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Image Feature Extraction

timm/vit_base_patch16_siglip_224.v2_webli

timm

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Image Feature Extraction

Octopus1/page-vitsplus

transformers

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Image Feature Extraction

TTPlanet/TTPLanet_SDXL_Controlnet_Tile_Realistic

273

diffusers

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Image Feature Extraction

timm/vit_small_patch16_dinov3_qkvb.lvd1689m

timm

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Image Feature Extraction

Mage-Fans/Mage-ViT

transformers

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Image Feature Extraction

Octopus1/page-vits

transformers

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Image Feature Extraction

timm/vit_pe_core_small_patch16_384.fb

timm

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Image Feature Extraction

timm/vit_7b_patch16_dinov3.lvd1689m

timm

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Image Feature Extraction

timm/vit_giant_patch14_dinov2.lvd142m

timm

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Image Feature Extraction

eugenehp/uni2

rlx

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Image Feature Extraction

facebook/dinov3-convnext-large-pretrain-lvd1689m

transformers

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Image Feature Extraction

apple/aimv2-large-patch14-224

transformers

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Image Feature Extraction

timm/vit_so400m_patch14_siglip_224.v2_webli

timm

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Jun 22, 2026200+ model pages and new retrieval deep-divesExpanded the model catalog with enriched pages (architecture, benchmarks, Mixpeek SDK examples, and pipeline pairings) across embedding, vision-language, video, audio, OCR, and reranking models: plus new vendor-neutral guides on Matryoshka embeddings, reasoning rerankers, and retrieval feedback loops.