News

Welcome new MCL Member Kaitai Zhang!

We are so happy to welcome a new Ph.D. student, Kaitai Zhang, this Fall 2017. Let us hear what he has to say about his research interests and about his impression of MCL.

Could you briefly introduce yourself and your research interests?

My name is Kaitai Zhang, and I am a 2nd year Ph.D. student in MCL lab at USC. Prior to joining MCL, I received my Bachelor’s degree of Physics at Fudan University. My research interests include machine learning, deep learning and computer vision.

What is your impression about MCL and USC?

I still remember the warm welcomes I received when I first join our MCL lab. People here are kind and always keep an enthusiastic attitude to research, which truly motivates me. Based on my first year here I love the environment at USC. I especially enjoy the little café across electrical engineering building. ^_^

What is your future expectation and plan in MCL?

As a junior Ph.D., my future expectation is to dedicate my time, thoughts and passion to conduct quality research work for the next five years. I also hope to build life-long friendships with the individuals in our lab.

By |October 15th, 2017|News|Comments Off on Welcome new MCL Member Kaitai Zhang!|

Welcome New MCL Member Fenxiao Chen

We are so happy to welcome a new Ph.D. student, Fenxiao Chen, in Fall 2017. Let us hear what she said about her research and MCL.

1. Could you briefly introduce yourself? (Previous research experience, project experience, research interest and expertise)
I worked on Cloud Computing and distributed systems before. I interned at Berkeley National Lab on DNA k-mer assembly and Artigen Corp on natural language processing.

2. What’s your first impression of USC and MCL?
First impression of USC is that it’s a school that welcomes a great range of diversity. MCL is the largest research group I have seen so far in the EE department. I like the researching environment that is not only encouraging but also inspiring.

3. What’s your future expectation for MCL?
I hope I can develop more expertise on natural language processing and deep learning. With the help of MCL I wish to bring my own contribution as well.

By |October 9th, 2017|News, Uncategorized|Comments Off on Welcome New MCL Member Fenxiao Chen|

Welcome New MCL Member Harry Yang

We are so happy to welcome a new Ph.D. student, Harry Yang, in Fall 2017. Let us hear what he said about his research and MCL.

1. Could you briefly introduce yourself and your research interests?
My name is Chao “Harry” Yang, and I am a 2nd year Ph.D. student at the MCL lab in the department of computer science at USC. Prior to joining MCL, I was a PhD student at the computer graphics lab of USC. I received my Bachelor’s degree of mathematics in University of Science and Technology of China. I am interested in computer vision and deep learning, and previously I worked on research projects related to image inpainting and domain adaptation.

2. What’s your first impression of USC and MCL?
USC has a beautiful campus and a vibrant research environment. I love to walk in the campus seeing a lot of students and professors full of passion and energy. The MCL lab is a wonderful place with a caring and supportive advisor and a large group of young talented students. I feel more motivated and enthusiastic about my everyday research after joining MCL and I super enjoy the interaction with the professor and group members.

3. What is your future expectation and plan in MCL?
I want to make friends in MCL, do good research and write high-quality papers. I am really excited to be able to learn from everyone in the group. With so much help and support, I am looking forward to a great career ahead of me after finishing my study in MCL.

By |October 1st, 2017|News, Uncategorized|Comments Off on Welcome New MCL Member Harry Yang|

MCL Students Presented Papers at BMVC 2017

We would like to share the good news that our group has two papers accepted by BMVC 2017 from Qin Huang and Siyang Li. This year BMVC is more competitive than before, according to the conference committee. We are happy that our group successfully has two papers, especially with one as oral presentation.

–Qin Huang, Chunyang Xia, Chihao Wu, Siyang Li, Ye Wang, Yuhang Song and C.-C. Jay Kuo, “Semantic Segmentation with Reverse Attention” (Oral)
–Siyang Li, Xiangxin Zhu, Qin Huang, Hao Xu and C.-C. Jay Kuo, “Multiple Instance Curriculum Learning for Weakly Supervised Object Detection” (Poster)

Here are the Obstructs for the two papers:

“Semantic Segmentation with Reverse Attention”:
Obstruct: Recent development in fully convolutional neural network enables efficient end-to-end learning of semantic segmentation. Traditionally, the convolutional classifiers aretaught to learn the representative semantic features of labeled semantic objects. In thiswork, we propose a reverse attention network (RAN) architecture that trains the net-work to capture the opposite concept (i.e., what are not associated with a target class) aswell. The RAN is a three-branch network that performs the direct, reverse and reverse-attention learning processes simultaneously. Extensive experiments are conducted toshow the effectiveness of the RAN in semantic segmentation. Being built upon theDeepLabv2-LargeFOV, the RAN achieves the state-of-the-art mean IoU score (48.1%)for the challenging PASCAL-Context dataset. Significant performance improvementsare also observed for the PASCAL-VOC, Person-Part, NYUDv2 and ADE20K datasets.

“Multiple Instance Curriculum Learning for Weakly Supervised Object Detection”:
Obstruct: When supervising an object detector with weakly labeled data, most existing ap- proaches are prone to trapping in the discriminative object parts, e.g., finding the face of a cat instead of the full body, due to lacking the supervision on the extent of full objects. To address this challenge, [...]

By |September 25th, 2017|News, Uncategorized|Comments Off on MCL Students Presented Papers at BMVC 2017|

Congratulations to Eddy Wu for Passing His Defense

Congratulations to Eddy Wu for passing his defense. His thesis title is “Deep Learning Techniques for Supervised Pedestrian Detection and Critically-Supervised Object Detection” with three major topics, as follow:

In the first topic, a boosted convolutional neural network (BCNN) system is proposed to enhance the pedestrian detection performance. Being inspired by the classic boosting idea, we develop a weighted loss function that emphasizes challenging samples in training a convolutional neural network (CNN). Two types of samples are considered challenging: 1) samples with detection scores falling in the decision boundary, and 2) temporally associated samples with inconsistent scores. Finally, we train a boosted fusion layer to benefit from the integration of these two weighting schemes. We test the corresponding BCNN on the Caltech pedestrian dataset in the experiment and observe a significant performance gain over the Fast-RCNN baseline.

In the second topic, a semi-supervised learning method is proposed for pedestrian detection in a domain adaptation setup. The proposed clustered deep representation adaptation (CDRA) method uses a small amount of labeled data to train an intial detector, extracts the deep representation and, then, clusters samples based on the space spanned by the deep representation. A purity measurement mechanism is applied to each cluster to provide a confident score to the estimated class of unlabeled data. Along with a weighted training approach, the CDRA method is shown to achieve the state-of-the-art performance against some large scale datasets.

In the third topic, we propose a new framework called critically-supervised learning that mimics children learing behaviors. Several novel components are proposed to fulfill the high level concept, including negative object proposal, critical example mining, and a machine-guided labeling process based on question answering. A labeling time model is proposed to [...]

By |September 18th, 2017|News|Comments Off on Congratulations to Eddy Wu for Passing His Defense|

Congratulations to Qin Huang for Passing His Defense

Congratulations to Qin Huang for passing his defense. His Ph.D. thesis is entitled ‘Machine Learning Techniques for Perceptual Quality Enhancement and Semantic Image Segmentation’. His research focuses include designing effective deep neural network structures and representative feature representations for traditional machine learning solutions. After graduation, Qin will join Facebook as Research Scientist for full-time position. His advices to the group members is to work hard, think more, be modest.

By |September 11th, 2017|News|Comments Off on Congratulations to Qin Huang for Passing His Defense|

Welcome New MCL Lab Member Shamim Samadi

We are so happy to welcome a new Ph.D. student, Shamim Samadi, in Fall 2017. Let us hear what she said about her research and MCL.

1. Could you briefly introduce yourself and your research interests?
My name is Shamim Samadi, and I am a Ph.D. student at the MCL lab in the department of Electrical Engineering at USC. Prior to joining MCL, I was a graduate student at the ECE department in NC State University, Raleigh, NC. I received my Bachelor’s degree in Electrical Engineering from Sharif University of Technology, Tehran, Iran. I am passionate about machine learning and have recently grown a lot of interest in deep learning. My research expertise is applied machine learning and signal processing.

2. What is your impression about MCL and USC?
With a cozy beautiful campus in the heart of Los Angeles, USC is a lively environment and a top school with an outstanding Engineering program, particularly in my major. The MCL lab at USC is an excellent platform for doing original innovative research in machine learning and computer vision, with a dynamic and inspiring atmosphere.

3. What is your future expectation and plan in MCL?
My goal is to build upon my current knowledge and expertise in machine learning and be able to make a contribution to the field.

By |September 3rd, 2017|News|Comments Off on Welcome New MCL Lab Member Shamim Samadi|

Welcome New MCL Lab Member Bin Wang

We are so happy to welcome a new Ph.D. student, Bin Wang, in Fall 2017. Let us hear what he said about his research and MCL.

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

My name is Bin Wang. I got my bachelor’s degree majoring in Electronic Information Engineer-ing(EIE) from University of Electronic Science and Technology of China (UESTC) as a distinction graduate in 2017. During Sept. 2015 – Jan. 2016, I have been an exchange student at EE Department of City University of Hong Kong (CityU). Last year summer, as a research intern which was fully funded by Mitacs, I worked at University of Ontario Institute of Technology(UOIT), Canada for three months focusing on image processing and robotics. My research interests include image processing, computer vision and deep learning.

2. What is your impression about MCL and USC?

After arriving in Los Angeles for about a month, I really enjoy the sunshine and the living environment. We can easily get anything we want around the USC campus. Also, USC is well equipped with convenient facilities, especially the new fitness center at the new USC village area. With the help of the members of MCL, I get used to everything quickly. My labmates are really friendly and hold an enthusiastic attitude on their own research area.

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

As a first year Ph.D. student, I hope my time can be fulfilled with efficiency and joy here at MCL. Meanwhile, hard-working and dedication are the keys to success. Hope I can do some achievements at the region of computer vision and deep learning in the coming future.

By |August 27th, 2017|News|Comments Off on Welcome New MCL Lab Member Bin Wang|

Welcome New MCL Lab Member Jiali Duan

We are so happy to welcome a new Ph.D. student, Jiali Duan, in Fall 2017. Let us hear what he said about his research and MCL.

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

I’m Jiali Duan from Chinese Academy of Sciences, who is passionate and enthusiastic about life and research, never cease to explore. From 2015.9-2016.3, I interned at AuthenMetric for Face Recognition and Liveness Detection. From 2014-2017, I worked closely with Prof. Stan Z, Li and published papers related to detection, face benchmark and video recognition. I also had an intern experience at Sensetime for image/video segmentation. In 2017, I was awarded with UCAS Presidential Award and Excellent Beijing Graduate. More information about me is also available at https://davidsonic.github.io/index/.

2. What is your impression about MCL and USC?

MCL is an exuberant, marvelous family, in which I have made acquaintances with people who are intelligent and hospitable. I’m also very fortunate to meet Prof. Kuo, a kind and gentle mentor, who has a strong belief and ideal about research. As for my impression about USC, I have never ceased to be awed by its aesthetic beauty and mysteriously stunning appeal. I especially enjoy the sunshine and Romanesque architecture here at LA.

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

I would like to dedicate myself to research in the next coming years, pursuing the brightest pearl on the crown of the academia. I hope that my efforts could contribute as much as possible to our lab. My future expectation about MCL is that all group members could fight together, for the prosperity of our lab.

By |August 20th, 2017|News|Comments Off on Welcome New MCL Lab Member Jiali Duan|

Welcome New MCL Lab Member Shuo Wang

We are so happy to welcome a new master student, Shuo Wang, in Fall 2017. Let us hear what he said about his research and MCL.

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

My name is Shuo Wang, a master student in the University of Southern California majoring in Electrical Engineering. I acquired my bachelor’s degree from Beihang University in June, 2016, and my major was the Electronic and Information Engineering, which is similar with the one in the USC. I am interested in the digital signal and image processing and concentrate on the development of the neural network from the time when I made my graduation project on the neural network in Beihang University. In the project, the artificial neural network (ANN) is applied to calculate the parameter of the antenna based on the feature of the electromagnetic field. Now, I am looking into the application of the convolutional neural network (CNN) on the signal and image processing and doing the research with Weihao and Matt to apply the CNN to do the multiple object tracking (MOT) in a video sequence.

2. What is your impression about MCL and USC?

Firstly, I am really impressed by the DEN in USC because it can help us to deeply understand the knowledge structure in a course, which helps us to build a system for the direction we studied. In fact, the DEN network is unbelievable for me because of its multiple functions. In addition, I was impressed by the advanced facilities (especially the GPU) when I entered the MCL at first. I originally applied my own computer to process the experiment, which is really difficult because it is always out of memory since the lack of [...]

By |August 13th, 2017|News|Comments Off on Welcome New MCL Lab Member Shuo Wang|