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Rama Chellappa
University of Maryland, College Park
964Publications
93H-index
42.8kCitations
Publications 970
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#1Arthita Ghosh (UMD: University of Maryland, College Park)H-Index: 3
#2Rama Chellappa (UMD: University of Maryland, College Park)H-Index: 93
We present an adversarial deep domain adaptation (ADA) approach for training deep neural networks that estimate 3D pose and shape of a human from a single image. Existing datasets of in-the-wild images of humans have limited availability of 3D ground truth. We propose a novel deep architecture for 3D pose estimation and leverage the variations in pose, body shape and background in the synthetic datasets to train our network. Using ADA we adapt our network to real human images by designing a pipe...
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We propose a new algorithm to incorporate class conditional information into the discriminator of GANs via a multi-class generalization of the commonly used Hinge loss. Our approach is in contrast to most GAN frameworks in that we train a single classifier for K+1 classes with one loss function, instead of a real/fake discriminator, or a discriminator classifier pair. We show that learning a single good classifier and a single state of the art generator simultaneously is possible in supervised a...
Inferring the latent variable generating a given test sample is a challenging problem in Generative Adversarial Networks (GANs). In this paper, we propose InvGAN - a novel framework for solving the inference problem in GANs, which involves training an encoder network capable of inverting a pre-trained generator network without access to any training data. Under mild assumptions, we theoretically show that using InvGAN, we can approximately invert the generations of any latent code of a trained G...
The papers in this special section examine compact and efficient feature representation and learning in computer vision.
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Aug 1, 2019 in IJCAI (International Joint Conference on Artificial Intelligence)
#1Yogesh Balaji (UMD: University of Maryland, College Park)H-Index: 7
#2Martin Renqiang Min (Princeton University)H-Index: 9
Last.Hans Peter Graf (Princeton University)H-Index: 29
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1 CitationsSource
#1Upal Mahbub (UMD: University of Maryland, College Park)H-Index: 10
#2Jukka Komulainen (University of Oulu)H-Index: 12
Last.Rama Chellappa (UMD: University of Maryland, College Park)H-Index: 93
view all 4 authors...
An empirical investigation of active/continuous authentication for smartphones is presented by exploiting users’ unique application usage data, i.e., distinct patterns of use, modeled by a Markovian process. Specifically, variations of hidden Markov models (HMMs) are evaluated for continuous user verification, and challenges due to the sparsity of session-wise data, an explosion of states, and handling unforeseen events in the test data are tackled. Unlike traditional approaches, the proposed fo...
4 CitationsSource
Urban material recognition in remote sensing imagery is a challenging problem due to the difficulty of obtaining human annotations, especially on low resolution satellite images. To this end, we propose an unsupervised domain adaptation-based approach using adversarial learning. We aim to harvest information from smaller quantities of high resolution data (source domain) and utilize the same to super-resolve low resolution imagery (target domain). This can potentially aid in semantic as well as ...
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#1Wei-An LinH-Index: 6
#2Haofu LiaoH-Index: 3
Last.Shaohua Kevin ZhouH-Index: 5
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Computed tomography (CT) is an imaging modality widely used for medical diagnosis and treatment. CT images are often corrupted by undesirable artifacts when metallic implants are carried by patients, which creates the problem of metal artifact reduction (MAR). Existing methods for reducing the artifacts due to metallic implants are inadequate for two main reasons. First, metal artifacts are structured and non-local so that simple image domain enhancement approaches would not suffice. Second, the...
Jun 9, 2019 in ICML (International Conference on Machine Learning)
#1Yogesh Balaji (UMD: University of Maryland, College Park)H-Index: 7
#2Hamed Hassani (UPenn: University of Pennsylvania)H-Index: 8
Last.Soheil Feizi-Khankandi (UMD: University of Maryland, College Park)H-Index: 15
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#1Chen Change Loy (NTU: Nanyang Technological University)
#2Xiaoming Liu (MSU: Michigan State University)H-Index: 38
Last.Rama Chellappa (UMD: University of Maryland, College Park)H-Index: 93
view all 5 authors...
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