MediaPipe Models and Model Cards

Face Detection
Face Mesh
Iris
Hands
Pose
Holistic
Selfie Segmentation
Hair Segmentation
Object Detection
Objectron
KNIFT

Face Detection

Short-range model (best for faces within 2 meters from the camera): TFLite model, TFLite model quantized for EdgeTPU/Coral, Model card
Full-range model (dense, best for faces within 5 meters from the camera): TFLite model, Model card
Full-range model (sparse, best for faces within 5 meters from the camera): TFLite model, Model card

Full-range dense and sparse models have the same quality in terms of F-score however differ in underlying metrics. The dense model is slightly better in Recall whereas the sparse model outperforms the dense one in Precision. Speed-wise sparse model is ~30% faster when executing on CPU via XNNPACK whereas on GPU the models demonstrate comparable latencies. Depending on your application, you may prefer one over the other.

Face Mesh

Face landmark model: TFLite model, TF.js model
Face landmark model w/ attention (aka Attention Mesh): TFLite model
Model card, Model card (w/ attention)

Iris

Iris landmark model: TFLite model
Model card

Hands

Palm detection model: TFLite model (lite), TFLite model (full), TF.js model
Hand landmark model: TFLite model (lite), TFLite model (full), TF.js model
Model card

Pose

Pose detection model: TFLite model
Pose landmark model: TFLite model (lite), TFLite model (full), TFLite model (heavy)
Model card