Generative adversarial networks (GANs) present a way to learn deep representations
without extensively annotated training data. These networks achieve learning through …

Large deep learning models are impressive, but they struggle when real-time data is not
available. Few-shot class-incremental learning (FSCIL) poses a significant challenge for …

Human-centric visual tasks have attracted increasing research attention due to their
widespread applications. In this paper, we aim to learn a general human representation from …

As an instance-level recognition problem, person re-identification (ReID) relies on
discriminative features, which not only capture different spatial scales but also encapsulate …

Object models are gradually progressing from predicting just category labels to providing
detailed descriptions of object instances. This motivates the need for large datasets which …

Abstract Person Re-identification (ReID) is to identify the same person across different
cameras. It is a challenging task due to the large variations in person pose, occlusion …