Search and RAG2026
OpenBMB · China
Embeddings for mixed-modality search: text, images and pages with text and a picture together land in one space, and a single text query can rank them in one shared list. Built on research showing that ordinary models prefer text over images. Language on the card: English.
- searching a catalog where some items are described by text and some by a picture
- searching slide decks and pages with diagrams
- RAG over a mixed knowledge base
- Sizes
- 2B (based on Qwen3-VL-2B)
- Hardware
- from: Laptop
Image generation2026
Sperid Labs · not stated
Generates images directly in pixels, without a compressed latent space. After fine-tuning, the same weights estimate depth from a single photo and restore and upscale images 4 times. Prompts are in English, the default size is 1024 by 1024.
- generating images from a description
- estimating scene depth from a single photo
- restoring and upscaling old or compressed photos
- Sizes
- 3B
- Hardware
- from: 1 GPU
Search and RAG2026
Tencent · China
Universal embeddings based on Qwen3.5: they turn text, images, video and visual documents into one vector of 4096 numbers. Audio is not supported. Languages on the card: Chinese and English.
- searching a product catalog by picture or description
- searching video and slide decks
- RAG over mixed text and image materials
- Sizes
- 2B и 9B
- Hardware
- from: Laptop
Medicine2026
MIT CSAIL, Massachusetts General Hospital and Harvard Medical School · USA
Finds 60 anatomical structures on an X-ray: ribs, vertebrae, pelvis and limb bones. They can be used to measure, for example, the curvature angle of the spine automatically. It does not look for pathologies and does not tell right from left.
- labeling anatomy on X-ray images
- measuring the spine curvature angle
- matching fluoroscopy frames with CT for navigation
- Sizes
- a small U-Net, 256 by 256 pixel images
- Hardware
- from: Laptop
Search and RAGOllama2025–2026
Google · USA
Small multilingual embeddings from Google that run on a phone or laptop without internet. The second version also understands images, video and audio in one vector space.
- On-device document search
- RAG without sending data outside
- Search over photos, video and audio by a text query
- Sizes
- 300M и 740M (EmbeddingGemma 2)
- Hardware
- from: Laptop
Plates and vehicles2020–2026
Mikel Brostrom (open project) · not disclosed
A set of trackers: it links the same vehicle across frames and cameras, which is how flow and time on site are counted. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Counting vehicles crossing a line
- Following a vehicle across frames
- Finding the same vehicle on another camera
- Sizes
- trackers plus re-identification models from compact to large
- Hardware
- from: Laptop
Autonomous driving2020–2026
comma.ai · USA
An open driver assistance system: a neural network keeps the lane and controls speed from a camera, plus a driver attention monitoring model. The models live right in the repository and are updated constantly.
- A research testbed for driver assistance systems
- Studying driver attention monitoring with an in-cabin camera
- Comparison with your own lane-keeping algorithms
- Sizes
- compact, designed for an in-vehicle device
- Hardware
- from: Laptop
3D2024–2026
NAVER LABS Europe · France (NAVER, South Korea)
The family that started "single-pass" 3D reconstruction from a pair or set of photos without camera calibration. MASt3R added point matching and scale; MUSt3R and BLASt3R added video support.
- 3D scene from several photos without calibration
- Point matching between images
- Mapping from video (SLAM)
- Sizes
- 0.57B – 0.69B
- Hardware
- from: Laptop
Drawings and CADRUGGUF2026
GreenMap · not disclosed
A set of small models for Russian-language construction drawings: it finds the drawing area, title block and legend, marks up walls and hatching, and pulls sheet data into JSON along with references to standards. A draft that an engineer checks.
- Finding the title block, legend and drawing area on a sheet
- Marking up walls and hatching on a floor plan
- Extracting drawing data into structured JSON
- Sizes
- 3.5M - 4B
- Hardware
- from: Laptop
Faces2021–2026
InsightFace (deepinsight) · China
The most widely used open toolkit for face detection and recognition. Many identity-preserving image generators are built on it. The pretrained weights are non-commercial.
- Detecting and comparing faces in photos
- Face-based access in prototypes
- Face processing as part of other AI systems
- Sizes
- packages from 16 MB to 407 MB
- Hardware
- from: Laptop
Plates and vehicles2026
Intel · USA
Intel models for vehicle video analytics: car, truck, bus, motorcycle, plus entry and exit logging and vehicles stopped too long. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Counting vehicles and splitting them by type
- Logging vehicle entry and exit
- Monitoring parking space occupancy
- Sizes
- YOLO26 variants from nano to x
- Hardware
- from: Laptop
Deepfake detection2023–2026
Adobe Research and University of Surrey · USA
An image watermark for arbitrary resolutions built for the Content Authenticity Initiative: it can both apply a mark and remove one. The detector errs in both directions - a human reviews the output.
- Marking images on the way out of your own pipeline
- Checking the provenance of a submitted image
- Linking with content provenance metadata
- Sizes
- model types Q and P with different mark capacity
- Hardware
- from: Laptop
Deepfake detection2025–2026
University of Michigan · USA
A lightweight detector of generated images, trained on 2.7M samples from nearly 5000 different generators. It errs in both directions: the result is a reason for a human to check, not proof.
- Checking submitted photos and illustrations
- Filtering AI images in a content flow
- Flagging suspicious images for manual review
- Sizes
- 22M
- Hardware
- from: Laptop
Computer vision2024–2026
Microsoft Research · USA
Reconstructs the 3D geometry of a scene from one photo: depth in meters, a point cloud and surface normals.
- Measuring rooms and objects from photos
- 3D point cloud from a single shot
- Preparing data for robots and AR
- Sizes
- ViT-S – ViT-G
- Hardware
- from: Laptop
Deepfake detection2023–2026
University of Wisconsin-Madison · USA
An early and still used approach: a simple classifier trained on top of a frozen CLIP that transfers to unseen generators. It errs in both directions - the output needs a human check.
- Checking images from new, unfamiliar generators
- A baseline when comparing detectors
- Fast rollout of a check without training a large model
- Sizes
- a linear classifier on top of CLIP ViT-L/14
- Hardware
- from: Laptop
Plates and vehicles2024–2026
ankandrew (open project) · not disclosed
Ready-made ONNX detectors that find the license plate in a frame, plus general object detectors. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Finding the plate in a camera frame
- Preparing a crop for character reading
- Picking frames with vehicles out of a video stream
- Sizes
- YOLO-v9 detectors at input sizes from 256 to 640 pixels
- Hardware
- from: Laptop
Image + text2023–2026
Shanghai AI Lab (OpenGVLab) · China
A family of video models: encoders for search and classification of clips, and chat models that analyze long videos. InternVideo 3 is designed for multi-hour recordings.
- Searching a video archive with a text query
- Action recognition in video
- Answering questions about a long recording
- Sizes
- small encoders – 9B
- Hardware
- from: Laptop
Computer vision2025–2026
Roboflow · USA
Real-time object detector, an open alternative to YOLO without AGPL. Supports segmentation (object outlines) and, since 2026, keypoints.
- Object detection in video and photos
- Precise outlines of parts and defects
- Fine-tuning for your own object classes
- Sizes
- Nano – 2XL
- Hardware
- from: Laptop
Computer vision2024–2026
Meta · USA
Meta's models for analyzing people in photos: pose keypoints, body part segmentation, normals and depth. Sapiens2 was trained at high resolution and adds human matting.
- Pose and body keypoint detection
- Segmentation of body parts and clothing
- Separating a person from the background
- Sizes
- 0.1B – 5B
- Hardware
- from: Laptop
3D2025–2026
Meta and the University of Oxford (VGG) · USA / UK
Reconstructs a 3D scene from one, several or hundreds of photos in seconds: camera positions, depth and a point cloud. Best Paper at CVPR 2025.
- 3D model of a room or object from a photo series
- Camera pose estimation for photogrammetry
- Point cloud for measurements and comparison with the plan
- Sizes
- about 1.2B
- Hardware
- from: 1 GPU
Plates and vehicles2025–2026
MorseTechLab · not disclosed
The most downloaded plate detector on Hugging Face: it finds the plate in a frame, and a separate model then reads it. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Finding the plate in camera video
- Preparing crops for plate reading
- Testing a plate recognition idea without training
- Sizes
- a fine-tuned YOLO11, with an ONNX build available
- Hardware
- from: Laptop
Plates and vehicles2024–2026
ankandrew (open project) · not disclosed
A ready pipeline for plate recognition: plate detector and character reading in one package, with your own models pluggable. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Getting plate recognition running quickly on site
- Automatic vehicle access by list
- Logging vehicle entry and exit
- Sizes
- a lightweight plate detector paired with XS and S reading models
- Hardware
- from: Laptop
Plates and vehicles2024–2026
ankandrew (open project) · not disclosed
Lightweight models that read characters from an already cropped license plate and run on an ordinary CPU. Filming vehicles and people and storing such records is personal data processing: agree the procedure and retention with a lawyer.
- Reading a plate at entry and exit
- Matching a plate against a whitelist of passes
- Going through archived camera footage
- Sizes
- XS and S models on the CCT architecture
- Hardware
- from: Laptop
Plates and vehicles2022–2026
PaddlePaddle (Baidu) · China
A ready set of models for vehicle tasks: plate recognition, car color and type, counting entries and exits, spotting parking where it is not allowed. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Counting traffic flow
- Identifying car type and color
- Reading the plate at the entrance
- Sizes
- a set of models: vehicle detector, attributes, plate reading on PP-OCR
- Hardware
- from: Laptop
Computer vision2023–2026
Meta · USA
Selects any object in photos and videos with a click or a box. The basis for background removal and object counting.
- Background removal from product photos
- Counting objects in photos
- Data labeling for training
- Sizes
- 91M – ~0,85B
- Hardware
- from: Laptop
Plates and vehicles2026
Autolane · not disclosed
A recent set of plate recognition weights: two plate detectors and a reading model, trained on US plates, so the Russian format needs fine-tuning. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Finding the plate in a frame
- Reading the plate characters
- Running on cameras and single-board computers
- Sizes
- RF-DETR and YOLOX-S detectors, CCT-S for character reading
- Hardware
- from: Laptop
Computer vision2023–2026
Ultralytics · USA
The most widely used real-time object detector: finds and marks items in video even on modest hardware. YOLOv5 came out back in 2020; the catalog starts from YOLOv8.
- Counting people, cars and goods on video
- Checking hard hats and workwear
- Spotting defects on the production line
- Sizes
- 2.4M – 68M
- Hardware
- from: Laptop
Computer visionGGUF2024–2025
ByteDance and the University of Hong Kong · China
Estimates depth, the distance to every point, from one ordinary photo or video. DA3 reconstructs scene geometry from several frames.
- Estimating distances and volumes from a camera
- Depth effects for photo and video
- Navigation for robots and drones
- Sizes
- 25M – 1.4B
- Hardware
- from: Laptop
3D2025
Tencent Hunyuan · China
Generates 3D human motion animation from a text description: the skeletal animation is ready for 3D editors and game engines. Understands English and Chinese.
- Character animation from a text description
- Draft animation for games and videos
- Motion library for avatars
- Sizes
- 0.46B – 1B
- Hardware
- from: 1 GPU
3D2025
Meta and Carnegie Mellon University · USA
A single model builds a metric 3D reconstruction from photos, and uses camera, depth or pose data when available. One weights variant is under Apache 2.0.
- 3D reconstruction of an object or room from photos
- Exporting the scene to COLMAP format for further processing
- Depth and camera pose estimation
- Sizes
- about 1.2B
- Hardware
- from: 1 GPU
Computer vision2025
Meta · USA
Meta's family of encoders for images and video, and with PE-AV also for audio. PE-Core searches by text more accurately than SigLIP 2 (per Meta); small versions are available.
- Search photos and videos by description
- Catalog labeling and tagging
- Search across audio and video (PE-AV)
- Sizes
- size not stated on the model card
- Hardware
- from: Laptop
3D2025
Shanghai AI Lab · China
Reconstructs a 3D scene and camera positions from a set of photos or a video without relying on a "reference" frame. Pi3X gives smoother point clouds and approximate scale in meters.
- 3D scene reconstruction from video
- Camera pose estimation from frames
- Point clouds for research and prototypes
- Sizes
- 0.96B – 1.4B
- Hardware
- from: 1 GPU
Computer vision2023–2025
Meta · USA
Meta's open reproduction of CLIP with a transparent data collection recipe. MetaCLIP 2 is trained on multilingual data from around the world. Non-commercial license only.
- Image search by text
- Image classification without training
- Search research and prototypes
- Sizes
- 0.15B – 3.6B
- Hardware
- from: Laptop
3DGGUF2025
Meta · USA
Reconstructs the 3D shape of an object or a human body from one ordinary photo, even when the object is partly hidden. Two models: Objects and Body.
- 3D model of an item from a catalog photo
- Estimating body pose and shape from a photo
- Try-on and AR scenarios
- Sizes
- size not stated on the model card
- Hardware
- from: 1 GPU
Computer vision2023–2025
IDEA Research · China
Finds any objects in an image from a text description, without training on your data: "red box", "person without a hard hat". Rex-Omni is the new VLM-based generation.
- Finding objects by description without labeling
- Automatic data labeling for training
- Checking photos against requirements
- Sizes
- 172M – 3B
- Hardware
- from: Laptop
Deepfake detection2023–2025
The Chinese University of Hong Kong, Shenzhen (SCLBD) · China
Dozens of open face-swap detectors for video and photo under one codebase with ready weights. A detector errs in both directions: its output is a reason for a human to check, not proof of a forgery.
- First-pass check of a submitted video or selfie
- Comparing several detectors on your own data
- Fine-tuning a detector for your own flow of applications
- Sizes
- Xception- and EfficientNet-class detectors, tens of millions of parameters
- Hardware
- from: Laptop
Computer vision2023–2025
Meta · USA
Foundation models that turn an image into a numeric "fingerprint". They are used to build similar-image search, classification and segmentation without large labeled datasets.
- Finding similar products and photos
- Image classification on small datasets
- Base for your own quality-control models
- Sizes
- 21M – 7B
- Hardware
- from: Laptop
Faces2025
ByteDance · China
Transformer-based face recognition from ByteDance, one of the most accurate open models on benchmarks. Weights are published in ONNX format but are non-commercial.
- Comparing faces and searching a photo database
- Research on recognition accuracy
- Access control prototypes
- Sizes
- ViT-T – ViT-L
- Hardware
- from: Laptop
Photo editingGGUF2024–2025
Nankai University · China
An open MIT-licensed model for precise object segmentation and background removal. RMBG-2.0 is built on it. Versions for 2K and for hair and semi-transparent edges.
- Bulk background removal from product photos
- Precise masks for design and print
- Cutting out people with hair for advertising
- Sizes
- about 220M (lightweight lite versions available)
- Hardware
- from: Laptop
Medicine2025
Google · USA
Google's lightweight encoder for medical images and text, the same one inside MedGemma. Sorts images and finds similar ones. Does not replace a doctor; decisions are made by a specialist.
- Finding similar images in a clinic's archive
- Pre-sorting images for a doctor
- A base for your own image classifiers
- Sizes
- about 0.9B
- Hardware
- from: Laptop
Deepfake detection2024–2025
Meta · USA
An image watermark that can be applied to individual regions: the model shows which part of the image is marked. It errs in both directions - a human reviews the result.
- Marking generated and edited images
- Finding a marked fragment inside a collage
- Tracking which parts of a picture were made by AI
- Sizes
- a mark encoder and decoder for images
- Hardware
- from: Laptop
Deepfake detection2024–2025
Xiaohongshu, USTC and Shanghai Jiao Tong University · China
An AI-image detector made of several experts: some look at visual artifacts, others at noise. The hard Chameleon benchmark was released with it. It errs in both directions - a human reviews the result.
- Checking realistic AI images without obvious artifacts
- Comparing detectors on hard examples
- Fine-tuning for your own type of content
- Sizes
- several experts based on ConvNeXt and CLIP
- Hardware
- from: 1 GPU
Deepfake detection2022–2025
GRIP, University Federico II of Naples · Italy
Finds traces of editing and shows on a map which regions of an image look altered: suitable for scans of contracts, certificates and photos of documents. It errs in both directions - a person decides.
- Checking scans of certificates and contracts for edits
- Highlighting altered photo regions for an expert
- Filtering out obviously redrawn documents before manual review
- Sizes
- a transformer model producing a map of suspicious regions
- Hardware
- from: 1 GPU
Moderation and safety2023–2025
Falconsai and Freepik · USA and Spain
Small models that tell explicit images from regular ones. The Freepik model distinguishes four levels of explicitness. They run on a CPU.
- Filtering user photos and avatars
- Checking generated images before publishing
- Labeling a media library
- Sizes
- 86M
- Hardware
- from: Laptop
Medicine2024–2025
Bioptimus · France
Pathology foundation models from France's Bioptimus with 1.1B parameters, plus the compact H0-mini. The first version is open under Apache 2.0. Does not replace a doctor; decisions are made by a specialist.
- Histology slide patch features for research models
- A prototype for sorting slides by tissue type
- Research projects linking morphology and molecular data
- Sizes
- 86M (H0-mini) – 1,1B
- Hardware
- from: Laptop
Plates and vehicles2023–2025
szad670401 (open project) · China
A well-known open system for Chinese plates: single-row blue and yellow plates, electric vehicles, driving-school cars. It has to be fine-tuned for the Russian plate format. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Plate recognition at entry and exit
- Running on modest hardware without a GPU
- Embedding recognition into your own application
- Sizes
- compact detection and reading models designed to run without a GPU
- Hardware
- from: Laptop
Computer-use agents2024–2025
Microsoft · USA
Breaks a screenshot down into buttons, fields and icons with labels so a regular language model can understand and control the screen. It does not click itself; it serves as the agent's eyes.
- Mapping legacy software screens for automation
- Preparing an agent to work in an interface
- Checking that the required elements are on screen
- Sizes
- under 1B (detector + captioning)
- Hardware
- from: Laptop
Computer vision2023–2025
Google · USA
Models that map images and text into a shared space: you can search photos by words and classify images without training. OpenAI's CLIP (2021) is the predecessor.
- Image search by text query
- Automatic catalog labeling and tagging
- Filtering prohibited content
- Sizes
- about 0.2B to 2B
- Hardware
- from: Laptop
Medicine2024–2025
Mahmood Lab (Mass General Brigham, Harvard) · USA
A foundation model for histology slides: turns patches of digital slides into features for tissue classification. Does not replace a doctor; decisions are made by a specialist.
- Research classifiers of tissue types from digital slides
- Finding similar cases in a slide archive
- Preparing features for research prognosis models
- Sizes
- about 300M (UNI) – about 680M (UNI2-h)
- Hardware
- from: Laptop
Computer vision2022–2025
University of Sydney and JD Explore Academy · Australia / China
A simple, accurate model for human pose estimation via keypoints. ViTPose++ handles human, animal and whole-body poses; built into the Transformers library.
- Body keypoints in photos and video
- Motion analysis in sports and rehabilitation
- Monitoring work postures and safety practices
- Sizes
- 33M – about 1B
- Hardware
- from: Laptop
Medicine2024
Mahmood Lab (Mass General Brigham, Harvard) · USA
Image-plus-text models for pathology: search slides by an English description, classify without fine-tuning; TITAN describes a whole slide. Does not replace a doctor; decisions are made by a specialist.
- Text-query search across a slide archive for research
- Draft slide descriptions for research projects
- Tissue classification without labels at the start of a study
- Sizes
- about 160M – 300M
- Hardware
- from: Laptop
Plates and vehiclesRU2022–2024
RIA.com · Ukraine
A plate recognition system with separate reading modules for Russia, Kazakhstan, Belarus, Ukraine, Georgia, Armenia and Kyrgyzstan. Filming vehicles and people and storing the records is personal data processing: agree the procedure with a lawyer.
- Reading a Russian plate from a camera
- Identifying the country and plate type
- Logging vehicles at entry and exit
- Sizes
- a YOLOv8 detector plus separate character-reading modules
- Hardware
- from: Laptop
Drawings and CAD2023–2024
Manycore Research · China
It assembles a 3D model of a product from three standard drawing projections - front, top and side - including cases where the lines in the drawing are incomplete. The output is a draft; an engineer checks and signs off the document.
- Turning a three-view drawing into a 3D model
- Digitising an archive of paper drawings for furniture and cabinets
- Checking that the views agree with each other
- Sizes
- size not stated on the model card, several checkpoints published for different inputs
- Hardware
- from: 1 GPU
Recommenders2024
Marqo · Australia
Models that turn a product photo and its title into a single vector: suitable for a similar-items block, image search and matching by description. Built for retail product cards.
- Similar items by photo and title
- Catalogue search by image
- Product search from a shopper phrase
- Sizes
- 203M (B) и 652M (L)
- Hardware
- from: Laptop
Plates and vehicles2023–2024
dima806 (open project) · not disclosed
Two simple photo classifiers: vehicle type and car brand. Trained on public datasets, so check them on your own footage before use. Filming vehicles and people is personal data processing: agree the procedure with a lawyer.
- Identifying the vehicle type from a photo
- Pre-labelling the car brand
- Going through photos in listings and applications
- Sizes
- based on ViT-base (google/vit-base-patch16-224-in21k)
- Hardware
- from: Laptop
MedicineNot maintained2024
Paige · USA
Paige's pathology foundation model, trained on millions of digital slides. The first version is Apache 2.0, the second is for research only. Does not replace a doctor; decisions are made by a specialist.
- Slide patch features for research classifiers
- Selecting slides for re-review in research projects
- Comparison with other pathology models on your own archive
- Sizes
- about 632M
- Hardware
- from: Laptop
Image + textNot maintained2024
Microsoft · USA
A very small vision model: captions, object detection, segmentation and text reading from a single prompt. Runs even on a CPU.
- Reading text in photos
- Finding and highlighting objects
- Automatic photo captions
- Sizes
- 0.23B – 0.77B
- Hardware
- from: Laptop
Deepfake detectionNot maintained2023–2024
Sichuan University and co-authors · China
An open model for finding forgeries in images: it outputs a pixel-level mask of altered regions. It errs in both directions; its map is a hint for an expert, not proof of a forgery.
- Finding pasted and erased fragments in photos
- Checking document scans for edits
- A baseline when comparing manipulation-localization models
- Sizes
- a Vision Transformer based model
- Hardware
- from: 1 GPU
RecommendersNot maintained2023
FashionCLIP research project (Farfetch data) · not disclosed
A time-tested model for clothing and footwear: it places an item photo and its description in one space, so it fits similar-item blocks and outfit matching. Fine-tuning for your own assortment is advisable.
- Similar items by photograph
- Building an outfit and matching add-ons
- Automatic tagging of clothing cards
- Sizes
- built on CLIP ViT-B/32
- Hardware
- from: Laptop
Computer visionNot maintained2021–2022
OpenAI · USA
The 2021 model that first linked images and text: search photos by words and classify them without training. English only; SigLIP 2 or PE are usually chosen today.
- Image search by text query
- Automatic tags for a catalog
- Finding similar images
- Sizes
- about 0.15B – 0.6B
- Hardware
- from: Laptop
Computer visionNot maintained2022
Microsoft · USA
From an image it works out what kind of document it is: resume, diploma, certificate, contract. Helps sort candidate file bundles by type. A human makes the decision about a candidate; automatic screening without review must not be used.
- Sorting incoming candidate documents by type
- Checking that a document package is complete
- Finding the right scan in an archive
- Sizes
- base and large versions
- Hardware
- from: Laptop
Computer visionRUNot maintained2022
Sber AI and SberDevices (ai-forever) · Russia
A Russian version of CLIP: matches images with Russian captions. Lets you search photos by description and sort images into categories without training.
- Product search by photo and by Russian description
- Sorting images into categories without labeling
- Checking that a photo matches its caption
- Sizes
- 150M – 430M
- Hardware
- from: Laptop
Deepfake detectionNot maintained2020
MiniVision Technology · China
Practically the only fully open weight set for single-frame face liveness: it tells a live person from a photo, a screen or a mask. It errs in both directions - a person must be able to appeal a rejection.
- Liveness check when signing in by selfie
- Protecting an access system from a photo on a phone
- A check during remote customer identification
- Sizes
- two models of about 1.8 MB each
- Hardware
- from: Laptop
