Supervision By Registration

Supervision-by-Registration: An Unsupervised Approach to Improve the Precision of Facial Landmark Detectors

Features

Computer Vision Research - Unsupervised improvement of facial landmark detectors.

zalandoresearch/fashion-mnist

This project is a computer vision benchmark and image classification dataset used to measure and compare the accuracy of machine learning models. It provides a standardized collection of labeled fashion product images and training data formatted to be compatible with the MNIST dataset structure. The dataset consists of fixed-dimension grayscale images and label-based category mappings, stored in a binary format. It includes pre-split training and testing sets and a static distribution to ensure consistent cross-model benchmarking. The repository supports image classification benchmarking and

agrimgupta92/sgan

912View on GitHub

Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018

ahangchen/TFusion

310View on GitHub

CVPR2018: Unsupervised Cross-dataset Person Re-identification by Transfer Learning of Spatio-temporal Patterns

abhimanyudubey/confusion

201View on GitHub

Code for the ECCV 2018 paper "Pairwise Confusion for Fine-Grained Visual Classification"