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Found 4 papers, 2 papers with code
Controllable Inversion of Black-Box Face Recognition Models via Diffusion
Face recognition models embed a face image into a low-dimensional identity vector containing abstract encodings of identity-specific facial features that allow individuals to be distinguished from one another.
Augmentation for small object detection
We evaluate different pasting augmentation strategies, and ultimately, we achieve 9. 7\% relative improvement on the instance segmentation and 7. 1\% on the object detection of small objects, compared to the current state of the art method on
Face Alignment Using K-Cluster Regression Forests With Weighted Splitting
In this work we present a face alignment pipeline based on two novel methods: weighted splitting for K-cluster Regression Forests and 3D Affine Pose Regression for face shape initialization.
Deep Alignment Network: A convolutional neural network for robust face alignment
Our method uses entire face images at all stages, contrary to the recently proposed face alignment methods that rely on local patches.
Ranked #4 on
Face Alignment
on 300W Split 2
(NME (inter-ocular) metric)
