Demo Face Filters
List of Facer AR SDK Demo Face Filters and technologies represented with them.
Face AR SDK release archives are supplied with a minimum built-in number of face filter (effects), all other Demo effects can be downloaded from this page.
| Filters | Technologies represented | Required packages |
|---|---|---|
 | Animation, Triggers | face_tracker |
 | Action units with blendshapes in the AR 3D Mask | face_tracker |
 | AR 3D Mask | face_tracker |
 | Simple effect that allow to set an image as the Background Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | background |
 | Background segmentation neural network, Blur Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | background |
 | Background segmentation neural network, Bokeh effect | face_tracker, background |
 | Transfer of facial expressions to the 3D model, AR 3D Mask | face_tracker |
 | Retouch, AR 3D Mask | face_tracker |
 | Animation, Triggers | face_tracker |
 | Background segmentation neural network, 3D environment cubemap texture, AR 3D Mask Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, background |
 | Display face recognition wireframe with landmarks | face_tracker |
 | Virtual glasses try-on | face_tracker |
 | Virtual Makeup API effect. See more in Effect API section. Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | See comment below the table* |
 | AR 3D Mask, Physics | face_tracker |
 | Effect with API for testing multiple neural networks work at the same time: Lips, Hair, Background, Hair and Skin Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, lips, skin, background, hair |
 | Background segmentation neural network, Animated texture, AR 3D Mask Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, background |
 | Morphing, AR 3D Mask | face_tracker |
 | Background segmentation neural network, Animated texture, AR 3D Mask Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, background |
 | Multi-face morphing example | face_tracker |
 | Animated texture, AR 3D Mask | face_tracker |
 | Background segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | background |
 | Full body segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | body |
 | Virtual eye lenses example Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, eyes |
 | Effect for eyelashes tracking debug | face_tracker |
 | Eyes segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, eyes |
 | Hand gestures detection example | hands |
 | Glases detection (neural network approach), AR 3D Mask | face_tracker, background |
 | Hair segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | hair |
 | Hair recoloring in multiple shades, Hair segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, hair |
 | Hair strands recoloring Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, hair |
 | Displays hand skelet model | hands |
 | Heart rate measurement (Pulse) technology example | face_tracker |
 | Shader-based image filter | face_tracker |
 | Lips segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, lips |
 | Glitter lipstick effect, lips segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, lips |
 | Shiny lipstick effect, lips segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker, lips |
 | Virtual nails try on fffect Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | hands |
 | Occlusion neural network used to define face collisions with different objects in the screen Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | face_tracker |
 | AR Ring demo effect Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | hands |
 | Face-to-phone distance measurement | face_tracker |
 | Skin segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage. | skin |
Legend
Online / Offline- Online face filters can be applied both for realtime work and photo. Offline face filters are designed to work only with photos (offline mode).- Click on filter name to download the effect.
- Required packages column lists the packages you must include within the app. For iOS package names follow this simple rule: face_tracker -> BNBFaceTracker etc.
* Makeup effect dependencies are configured during runtime according to features enabled. You will see in log which package is missing in case of error.