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Could you briefly introduce yourself and your research interests?

My name is Zheng Wen, I’m currently pursuing my Master’s degree at USC in Electrical Engineering. I received my Bachelor’s degree in Beihang University, Beijing, China. I’m very curious in math and programming. I found it interesting to do something related matrix and machine learning, so I’m very glad that I Professor Kuo could give me this opportunity to join MCL and dive deeper in image processing, computer vision and machine learning.

What is your impression about MCL and USC?

This is my first year in USC, I found the campus is very beautiful even though kind of small. Leavey Library is a good place to study when we are struggling for the final exams of a semester. I really enjoy the American Chinese cuisine offered by the canteen. MCL is a big family. I get to know the members in MCL by EE569, Professor Kuo is an expert in multimedia, and his understanding in deep learning impressed me a lot. TAs are very experience in image processing and willing to help us.

What is your future expectation and plan in MCL?

In MCL, I want to do some project in image forensics with the help of Yao, learn more about image processing and machine learning, also sharpen my programming skills and make some progress to the domain. I will try my best to get involved in MCL and make friends with everyone.

1. Could you briefly introduce yourself and your research interests?

My name is Chengyao Wang and I’m currently pursuing a M.S. degree in Electrical Engineering here at USC. Prior to that, I received my B.S. in Automation from Zhejiang University in 2018. With my interest lying in machine learning and computer vision, I’m now working on a summer intern project regarding classification and segmentation of medical images under the guidance of Prof. Kuo. I believe it will be a good starting point of exploring this intriguing area.

2. What is your impression about MCL and USC?

USC is well known for its academic achievements and strong alumni network, and it sure is. Everyone I met here is full of passion about what they’re doing and seems to be always ready to help others. MCL is such a dynamic and cohesive group, where everyone here could get a chance & full support to dig into their own areas of interest. Prof. Kuo is a respected expert with profound domain knowledge as well as a supportive instructor who knows well how to guide students and group people.

3. What is your future expectation and plan in MCL?

At this point, I would hope my current project goes on well and treat it with full devotion. I also want to connect with more people at MCL as a newcomer and blend into this warm and big family. Frankly speaking, I don’t have a clear vision for the future yet, but I believe I’ll stick to what I feel is interesting and make some differences.

1. Could you briefly introduce yourself and your research interests?

My name is Vasileios Magoulianitis and I was born in Athens, Greece. I joined Viterbi School of USC in Spring 2020, pursuing a Master’s degree on Machine Learning and Data Science. I graduated from the Electrical Engineering department at the University of Thessaly, receiving my bachelor’s degree with honors. At that time, my research interests were focused on video compression and its efficient implementations. The last year of my undergraduate studies, I interned at Irida Labs s.a., where I had my first experience with image processing and computer vision algorithms. Before joining USC, I had been working as a research assistant for the Centre of Research and Technology Hellas (CERTH), participating in EU-funded projects. My current research interests revolve around image processing and computer vision, as well as machine learning.

2. What is your impression about MCL and USC?

Since my first days in MCL, I have been impressed about the atmosphere exists in the lab. It maintains a multi-cultural environment that brings together highly talented students with different backgrounds. The knowledge sharing quality is at top level and there exists an underlying energy that pushes everyone to achieve at his top potentials. The learning curve of students in MCL grows really fast, since everyone is willing to help each other and to share his research ideas and suggestions. Professor Kuo collaborates and communicates firmly with his students, showing that he cares about the people in his lab. I would like to take this chance to express my gratitude to him for giving me the chance to work in such a reputable lab. USC and MCL is the right place to carry out research and explore also [...]

Abstract of thesis:

The world around us is highly structured. Images not only contain various object categories with complex scenes but also include relationships between different objects or between humans and objects.  In recent years, deep learning has made a lot of achievements to the computer vision community, in both visual recognition and image generation tasks. In this thesis, we mainly leverage structure information to enhance the visual generation and understanding of these computer vision tasks.

On the visual generation side, image inpainting is the task to reconstruct the missing region in an image with plausible contents based on its surrounding context. In order to overcome the difficulty to directly learn the distribution of high-dimensional image data, we first divide the task into inference and translation as two separate steps and leverage the semantic information to help refine the textures. Second, we propose to introduce the semantic segmentation information, which disentangles the inter-class difference and intra-class variation to improve the quality of the generated images. On the visual understanding side, we study the problem of novel human-object interaction (HOI) detection, which is to recognize the relationship between humans and objects in images. We formulate it as a domain generalization problem and propose a unified framework of domain generalization to learn object-invariant features for predicate prediction, aiming at improving the generalization ability of the model to unseen scenarios. Finally, we provide some interesting research directions which can be addressed in the future.

Ph.D. experience:

I would like to express my gratitude to my advisor Professor C.-C. Jay Kuo for the continuous support of my Ph.D. study during these years. He has given me the freedom to pursue various projects without objection, and he has also provided insightful discussions about the [...]