Person recognition aims at recognizing the same identity across time and space with complicated scenes and similar appearance.
We build CSI-Net, a unified Deep Neural Network~(DNN), to learn the representation of WiFi signals.
In this work, we aim to move beyond such limitations and propose a new framework to leverage context for person recognition.
Recent years have witnessed increasing attention in cartoon media, powered by the strong demands of industrial applications.
DOMAIN ADAPTATION FACE DETECTION FACE RECOGNITION IMAGE CLASSIFICATION PERSON RECOGNITION
Person re-identification (re-ID) and attribute recognition share a common target at learning pedestrian descriptions.
Ranked #45 on
Person Re-Identification
on DukeMTMC-reID
With the aim of studying how current multimodal algorithms based on heterogeneous sources of information are affected by sensitive elements and inner biases in the data, we propose a fictitious automated recruitment testbed: FairCVtest.