Tianhorng Chang Received Posthumous PhD Degree

Tianhorng Chang, an MCL alumnus, entered the PhD/EE program at USC in Spring 1989, passed his screening exam on December 4, 1989, and became the third PhD student of Dr. Kuo in Spring 1990. Tianhorng took his qualifying exam on May 7, 1992. He was originally scheduled to take his defense in 1993. However, he could not do it but passed away in 1994 because of cancer.

Tianhorng Chang completed 46 units at USC and transferred in another 30 units from his previous MSEE program at the University of Florida. His graduate GPA at USC was 3.93. His seminal paper titled with “Texture Analysis and Classification with Tree-Structured Wavelet Transform” published by IEEE Trans. on Image Processing (1993) received 2000 citations. Due to Tianhorng’s near-complete curriculum and impactful research, USC granted Tianhorng’s posthumous PhD degree in 2018 August.

Tianhorng received his BSEE degree from the National Tsinghua University, Taiwan, in 1983. A ceremony to award the posthumous PhD degree to Tianhorng’s family was held in the National Tsinghua University on November 18, 2018. Many of his undergraduate classmates and MCL alumni in Taiwan attended the award ceremony. During the ceremony, Professor Kuo and several participants shared their memory on Tianhorng. A video clip featuring short speeches given by Professor Richard Leahy (the current Chair of USC/EE), Professor Sandeep Gupta (the former Chair of USC/EE) and Ms. Diane Demetras was also played. Tianhorng’s younger brother received the posthumous PhD degree on behalf of his family. The whole ceremony took about 1 hour.

Professor Kuo said, “Hope this award ceremony brings some comfort to Tianhorng’s family and Tianhorng’s story will encourage a younger generation to pursuit advanced research as long as they have strong passion.”

By |November 18th, 2018|News|Comments Off on Tianhorng Chang Received Posthumous PhD Degree|

MCL Research on Unsupervised Video Object Segmentation

One major technique debt in video object segmentation is to label the object masks for training instances. As a result, we propose to prepare inexpensive, yet high quality pseudo ground truth corrected with motion cue for video object segmentation training. Our method conducts semantic segmentation using instance segmentation networks and, then, selects the segmented object of interest as the pseudo ground truth based on the motion information. Afterwards, the pseudo ground truth is exploited to finetune the pretrained objectness network to facilitate object segmentation in the remaining frames of the video.  We show that the pseudo ground truth could effectively improve the segmentation performance. This straightforward unsupervised video object segmentation method is more efficient than existing methods. Experimental results on DAVIS and FBMS show that the proposed method outperforms state-of-the-art unsupervised segmentation methods on various benchmark datasets. And the category-agnostic pseudo ground truth has great potential to extend to multiple arbitrary object tracking.

Our goal is to segment the primary video object without manual annotations. The proposed method does not use the temporal information of the whole video clip at once but one frame at a time. Errors from each consequent frame do not propagate along time. As a result, the proposed method has higher tolerance against occlusion and fast motion. We evaluate the proposed method extensively on the DAVIS dataset the FBMS dataset. Our method gives state-of-the-art performance in both datasets with the mean intersection-over-union (IoU) of 79.3% on DAVIS, and 77.9% on FBMS.

This paper will appear in Asian Conference on Computer Vision (ACCV) 2018.


–By Ye Wang

By |November 11th, 2018|News|Comments Off on MCL Research on Unsupervised Video Object Segmentation|

MCL Research on High Quality Image Inpainting

Image inpainting is the task to reconstruct the missing region in an image with plausible contents based on its surrounding context, which is a common topic of low-level computer vision. Making use of this technique, people could restore damaged images or remove unwanted objects from images or videos. In this task, our goal is to not only fill in the plausible contexts with realistic details but also make the inpainted area coherent with the contexts as well as the boundaries.

In spite of recent progress of deep generative models, generating high-resolution images remains a difficult task. This is mainly because modeling the distribution of pixels is difficult and the trained models easily introduce blurry components and artifacts when the dimensionality becomes high. Following [1] which proposes to synthesize an image based on joint optimization of image context and texture constraints, we divide the task into inference and translation as two separate steps and model each step with a deep neural network [2]. We also use simple heuristics to guide the propagation of local textures from the boundary to the hole. Meanwhile, we introduce a novel block-wise procedural training scheme to stabilize the training and propose a new strategy called adversarial annealing to reduce the artifacts [3].

On the other hand, we observe that existing methods based on generative models don’t exploit the segmentation information to constrain the object shapes, which usually lead to blurry results on the boundary. To tackle this problem, we propose to introduce the semantic segmentation information, which disentangles the inter-class difference and intra-class variation for image inpainting [4]. This leads to much clearer recovered boundary between semantically different regions and better texture within semantically consistent segments. Experiments on multiple public datasets show [...]

By |November 4th, 2018|News|Comments Off on MCL Research on High Quality Image Inpainting|
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    MCL Director, Dr. C.-C. Jay Kuo, Delivered Distinguished Lectures in Singapore

MCL Director, Dr. C.-C. Jay Kuo, Delivered Distinguished Lectures in Singapore

MCL Director, Professor Kuo, was invited to give four distinguished lectures at three universities in Singapore in the week of October 22-26, 2018.

Dr. Kuo’s trip to Singapore was supported by the College of Engineering of the Nanyang Technological University (NTU) under the program of “Distinguished Speaker in FY2018”. The NTU is an autonomous research university in Singapore. It is known for its eco-friendly and smart technology garden campus — one of the most beautiful school campuses in the world. The University has over 33000 students, organized into eight colleges and schools.

Dr. Kuo delivered two Distinguished Lectures at the NTU. The title of his first lecture was “A Data-Driven Approach to Image-Splicing Localization” and that of his second lecture was “Interpretable Convolutional Neural Networks via Feedforward Design”. The first lecture was built upon recent research work of Ronald Salloum, who is a senior PhD student at MCL. The second lecture was based on Dr. Kuo’s recent research with four MCL members (Min Zhang, Siyang Li, Jiali Duan and Yueru Chen) as collaborators. Both lectures were well received.

Dr. Kuo also visited the National University of Singapore (NUS) and the Singapore University of Technology and Design (SUTD) during his short stay in Singapore. His visit to SUTD was hosted by Professor Ngai-Man Cheung who is an SIPI alumnus (see the accompanying photo with the news.)

By |October 28th, 2018|News|Comments Off on MCL Director, Dr. C.-C. Jay Kuo, Delivered Distinguished Lectures in Singapore|

Farewell to Dr. Xinfeng Zhang and Dr. Chao Yang

Dr. Xinfeng Zhang and Dr. Chao Yang are currently Postdoctoral Research Fellows at the MCL. They will complete their one-year stay and go back to China at the end of October.

Dr. Xinfeng Zhang received his PhD degree from Institute of Computing Technology, Chinese Academy of Sciences while Dr. Chao Yang received his PhD degree from Shanghai University. They are both experts in video coding. They joined the MCL in November 2017 and participated in two industrial projects: “Perceptual Video Coding based on Visual Attention Mechanism” (sponsored by Huawei) and “Joint Image Coding and Visual Understanding” (sponsored by Netflix, Tencent and Mediatek). They have done an excellent job in both projects, which leads to two journal papers under review.

MCL Director, Dr. C.-C. Jay Kuo, said that “It is our great pleasure to have Dr. Zhang and Dr. Yang to be around in our lab for the last year. They have made very important contributions. I do wish them the very best in their future career development.”

Dr. Xinfeng Zhang said that “It is a wonderful year for me in MCL, which is a prestigious research lab but also a family with love. I appreciate Prof. Kuo very much for the professional advices in my research, the strong support for my faculty job applications and the sincere guidance for life and career.  Moreover, I am very pleased to know all of the MCL members and become friends with you. Especially, thank Prof. Li, Dr. Yang, Haiqiang for the good research cooperation, and thank Bing Li and Bin Wang for the helps in my life of USC. Thanks, and best wishes for our MCL members!”

And Dr. Chao Yang said that “It’s a great honor to be here working [...]

By |October 21st, 2018|News|Comments Off on Farewell to Dr. Xinfeng Zhang and Dr. Chao Yang|
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    MCL Director, Dr. C.-C. Jay Kuo, Delivered Viterbi Special Guest Speech at Technion, Israel Institute of Technology

MCL Director, Dr. C.-C. Jay Kuo, Delivered Viterbi Special Guest Speech at Technion, Israel Institute of Technology

After a short stay in Athens for ICIP 2018, Professor Kuo flew to Israel and visited Technion, Israel Institute of Technology.  He delivered the Viterbi Special Guest Lecture titled with “Unveil Convolutional Neural Networks and Go Beyond” on October 11. The talk was very well received.

The Technion – Israel Institute of Technology – is a public research university in Haifa, Israel. The university was established in 1912 during the Ottoman Empire, which was more than 35 years before the State of Israel. The Technion is the oldest university in Israel. It is ranked the best university in Israel and in the whole of the Middle East.

There is a close tie between USC and Technion through Dr. Andrew J. Viterbi. Dr. Viterbi received a Technion Honorary Doctorate in 2000. He has been a Distinguished Visiting Professor of Electrical Engineering at the Technion since then. Dr. Viterbi announced a $50 million gift to secure and enhance the Technion-Israel Institute of Technology’s leadership position in electrical and computer engineering in Israel and globally in 2015. He is a member of the Technion Board of Governors.

Professor Kuo said, “It was my great honor to have this opportunity to be a bridge between the USC Viterbi School of Engineering and the Technion Viterbi Faculty of Electrical Engineering. It is very meaningful to have more interactions and faculty/student exchanges between these two world top universities.” Professor Kuo’s visit was sponsored by the Technion Rubiner/Viterbi Fund. He used the same office of Dr. Andrew Viterbi during his stay. Professor Kuo’s visit was hosted by Professor Josh Zeevi, who is a world renowned expert in vision and image sciences.

By |October 14th, 2018|News|Comments Off on MCL Director, Dr. C.-C. Jay Kuo, Delivered Viterbi Special Guest Speech at Technion, Israel Institute of Technology|
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    Professor Kuo Delivered Plenary Speech on Interpretable CNNs at ICIP 2018

Professor Kuo Delivered Plenary Speech on Interpretable CNNs at ICIP 2018

The 25th IEEE International Conference on Image Processing (ICIP) was held in the Megaron Athens International Conference Centre, Athens, Greece, from October 7-10, 2018. ICIP is the world’s largest and most comprehensive technical conference focused on image and video processing and computer vision. The theme of ICIP 2018 will be “Imaging beyond imagination”. The conference features world-class speakers, tutorials, exhibits, and a vision technology showcase.

MCL Director, Professor C.-C. Jay Kuo, delivered the Plenary Speech entitled with “Unveil Convolutional Neural Networks (CNNs) and Go Beyond” on Oct. 8, 2018. Professor Kuo has worked on theoretical understanding of CNNs since 2015 and published a sequence of papers on this topic. This speech contained main results of his research endeavor.

Specifically, Professor Kuo described a new interpretable feedforward CNN design methodology. It does not demand any backpropagation. This design adopts a data-centric approach and derives network parameters of the current layer based on data statistics from the output of the previous layer. This process continues layer after layer in one pass. The feedforward design leads to a CNN that has a classification performance close to the one designed by backpropagation. Yet, it is more robust with respect to adversarial attacks. Above all, it is mathematically transparent.

Professor Kuo has a paper entitled with “Interpretable Convolutional Neural Networks via Feedforward Design” as the main reference. It can be downloaded from the arXiv:

By |October 8th, 2018|News|Comments Off on Professor Kuo Delivered Plenary Speech on Interpretable CNNs at ICIP 2018|

Welcome New MCL Member Thiyagarajan Ramanathan

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

I’m pursuing my Master Degree in Electrical Engineering at USC with specialization in Image Processing and Machine Learning. I joined MCL in August 2018. My current research interests lie in the field of Machine Learning for Image Processing applications. I have worked on many applications of image processing such as Object detection, Vehicle tracking and Behavioral cloning using Deep models. I’m very interested in Natural Language Processing as well.

2. What is your impression about MCL and USC?

USC has been an amazing environment for my growth. Though I have been here only for a year, I have gained so much of knowledge and I’m very grateful to USC for that. The people at MCL are forward-thinking and very intelligent. The research at MCL is cutting edge and I am very happy and excited to be a part of the lab.

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

I want to interact more with Professor Kuo and all the students of the lab. I want to improve my research skills and expand my knowledge.

By |September 30th, 2018|News|Comments Off on Welcome New MCL Member Thiyagarajan Ramanathan|

Welcome New MCL Member Manasa Manohara

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

I am Manasa Manohara, a Master’s student at USC pursuing EE with a focus on Computer Vision. I finished my Bachelor’s from M.S.Ramaiah Institute of Technology in Bangalore, India. I worked as a Development Consultant at SAP India for about a year before I joined USC. I am excited about Computer Vision and Machine Learning, and how a combination of these technologies can be applied to solve everyday problems. I am particularly interested in Image and video segmentation and reconstruction. In my free time, I love to dance and read books.


2. What is your impression about MCL and USC?

USC provides a lot of opportunities for the students to grow not just in terms of academics but also encourages to pursue their personal interests.  It has a good mix of people who are passionate about what they do. I hope I can make the most of what USC has to offer.

MCL is doing a lot of good work in the field of Computer Vision and I would love to learn and contribute to their research along with interacting with my peers to explore their fields of interest.


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

I hope I can enhance my skills in the fields of Image Processing and Deep learning. I wish to accelerate and solve everyday persistent problems with an exciting mixture of the above technologies.


By |September 23rd, 2018|News|Comments Off on Welcome New MCL Member Manasa Manohara|

Welcome New MCL Member Abinaya Manimaran

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

I am Abinaya Manimaran, a second year Electrical Engineering graduate student. Before joining USC, I enjoyed working as a Researcher for 3 years at TCS Innovation Labs, India. I was introduced to many Machine Learning algorithms and was always excited to choose the right one to train a desired model. Having joined USC, I am concentrating to learn more in the field of Computer Vision and Machine Learning. I am interested in solving real-world problems that can help mankind be at a better place!


2. What is your impression about MCL and USC?

I see MCL as set of hard working and kind students led by experienced Prof Kuo. I like the way how everything is organized, from lab’s website to weekly meetings!

USC is known for very deep course works. Especially when it comes to Electrical Engineering, most of the courses are math intense, which helps in understanding the basics better. Both USC and MCL has a great Alumni network too!


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

I would be working on SAAK Transform as a new architecture for deep neural network and its applications in Computer Vision. My plan is to greatly strengthen my skills in this field. I am hoping at the end of my research, I would stand out both personally and professionally.

By |September 16th, 2018|News|Comments Off on Welcome New MCL Member Abinaya Manimaran|