The Visual Computing Lab (VClab) at Seoultech is dedicated to the design of a novel visual system for machines and robots. We are always looking for motivated graduate students. Prospective students looking for research opportunities, please, click here. Current areas of specific interest are (1)Surveillance Camera, (2) VR/AR Content Generation, (3) Robot Vision.
Person re-identification re-ID (re-ID) aim is to match the same person across different camera views. In recent years, make a lot of progress in re-ID, however, these are confined to short-term re-ID. Unlike, long-term re-ID, in the short-term re-ID, the clothes of each person are not changing, while real-world person change their clothes over time. Therefore, in long-term re-ID, extracting body size, hair color, and other id-relate features is important.
Big data has enabled deep learning algorithms achieve rapid advancements. In particular, state-of-the-art generative adversarial networks (GANs) are able to generate high-ﬁdelity natural images of diverse categories. They are widely general methods, now starting to be applied to several other important problems, such as semisupervised learning, stabilizing sequence learning methods for speech and language, and 3D modelling. However, they still remain remarkably difficult to train, with most current papers dedicated to heuristically finding stable architectures. We are looking for a new direction designed to avoid the instability issues in GANs,
Object placement aims to paste the foreground on the background with suitable location, size, and shape. In previous works, object placement is used as data augmentation strategy to facilitate the downstream tasks (e.g., object detection, segmentation). There are two common methods, i.e., splicing and copy-move, to generate new composite images. Splicing is cropping the foreground object from one image and pasting it on another background image. Copy-move is removing the foreground object with inpainting techniques and pasting the foreground object at another place in the same image