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.

Filter Name	Technologies represented	Online	Filter Icon	Required packages
0003_cu_Spider1_v3_b1	Animation, Triggers	Yes		face_tracker
ActionunitsGrout	Action units with blendshapes in the AR 3D Mask	Yes		face_tracker
Afro	AR 3D Mask	Yes		face_tracker
Background_doc	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.	Yes		background
blur_bg	Background segmentation neural network, Blur Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		background
blur_bg_2	Background segmentation neural network, Blur using bilateral filter Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		background
bokeh	Background segmentation neural network, Bokeh effect	No		face_tracker, background
BulldogHarlamov	Transfer of facial expressions to the 3D model, AR 3D Mask	Yes		face_tracker
BurningMan2018	Retouch, AR 3D Mask	Yes		face_tracker
CartoonOctopus	Animation, Triggers	Yes		face_tracker
CubemapEverest	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.	Yes		face_tracker, background
DebugWireframe	Display face recognition wireframe with landmarks	Yes		face_tracker
Glasses	Virtual glasses try-on	Yes		face_tracker
Makeup	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.	Yes		See comment below the table*
MonsterFactory	AR 3D Mask, Physics	Yes		face_tracker
nn_api	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.	Yes		face_tracker, lips, skin, background, hair
PineappleGlasses	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.	Yes		face_tracker, background
PoliceMan	Morphing, AR 3D Mask	Yes		face_tracker
Rorschach	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.	Yes		face_tracker, background
scene_4_faces	Multi-face morphing example	Yes		face_tracker
Skydiver	Animated texture, AR 3D Mask	Yes		face_tracker
test_BG	Background segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		background
test_Body	Full body segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		body
test_Eye_lenses	Virtual eye lenses example Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		face_tracker, eyes
test_Eyelashes	Effect for eyelashes tracking debug	Yes		face_tracker
test_Eyes	Eyes segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		face_tracker, eyes
test_gestures	Hand gestures detection example	Yes		hands
test_Glasses	Glases detection (neural network approach), AR 3D Mask	Yes		face_tracker, background
test_Hair	Hair segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		hair
test_Hair_bound	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.	Yes		face_tracker, hair
test_Hair_strand	Hair strands recoloring Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	No		face_tracker, hair
test_HandSkelet	Displays hand skelet model	Yes		hands
test_heart_rate	Heart rate measurement (Pulse) technology example	Yes		face_tracker
test_image_process_cartoon	Shader-based image filter	Yes		face_tracker
test_Lips	Lips segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		face_tracker, lips
test_Lips_glitter	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.	Yes		face_tracker, lips
test_Lips_shine	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.	Yes		face_tracker, lips
test_Nails	Virtual nails try on fffect Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		hands
test_Occl (iOS only)	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.	Yes		face_tracker
test_Ring	AR Ring demo effect Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		hands
test_Ruler	Face-to-phone distance measurement	Yes		face_tracker
test_Skin	Skin segmentation neural network Face filter performance can be lower on mid-end and low-end devices due to neural network usage.	Yes		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.