About
Reasoning about perceiving while better perceiving reasoning.
I recently graduated with a PhD from the ECE department at Carnegie Mellon University. Here is my PhD thesis. My current interests lie broadly in the intersection of perception, computer vision and deep learning. I worked with Prof. Marios Savvides, at the CyLab Biometrics Center. I also occasionally collaborated with Prof. Ole Menshoel. Some of my work was inspired by the work of and discussions with Prof. Tomaso Poggio.
Much of my work is centered around the problem of perception and representation learning. Building useful representations of data is of paramount importance. Ideally, a single good representation would be useful for any task one is interested in. Towards this goal, representations that are invariant to nuisance within-class transformations and that are discriminative towards between class transformations are useful. Some of my work has explored learning such representations by building invariant kernel classifiers, loss functions that promote such invariance and finally inductive biases in network architectures that explicitly promote invariance during feedforward computations. Self-supervision has also emerged as a promising class of techniques that promote rich representation learning through pretext tasks. Some of my work aims to provide a better understanding of the phenomenon of self-supervision paving the way for the development of more effective techniques. Finally, a few of my studies have dealt with inverse problems from the deep learning and randomized sparse signal approximation perspective.
More recently, some of my work sheds light on the role of random connectomes in the cortex and their effectiveness for perception. There ideas seem to have useful consequences for both deep learning and computational neuroscience.
I recently graduated with a PhD from the ECE department at Carnegie Mellon University. Here is my PhD thesis. My current interests lie broadly in the intersection of perception, computer vision and deep learning. I worked with Prof. Marios Savvides, at the CyLab Biometrics Center. I also occasionally collaborated with Prof. Ole Menshoel. Some of my work was inspired by the work of and discussions with Prof. Tomaso Poggio.
Much of my work is centered around the problem of perception and representation learning. Building useful representations of data is of paramount importance. Ideally, a single good representation would be useful for any task one is interested in. Towards this goal, representations that are invariant to nuisance within-class transformations and that are discriminative towards between class transformations are useful. Some of my work has explored learning such representations by building invariant kernel classifiers, loss functions that promote such invariance and finally inductive biases in network architectures that explicitly promote invariance during feedforward computations. Self-supervision has also emerged as a promising class of techniques that promote rich representation learning through pretext tasks. Some of my work aims to provide a better understanding of the phenomenon of self-supervision paving the way for the development of more effective techniques. Finally, a few of my studies have dealt with inverse problems from the deep learning and randomized sparse signal approximation perspective.
More recently, some of my work sheds light on the role of random connectomes in the cortex and their effectiveness for perception. There ideas seem to have useful consequences for both deep learning and computational neuroscience.
Academic Services
Regularly serve as a reviewer for TPAMI, TIP, NeurIPS, ICML, CVPR, ICCV, ECCV, ACCV, WACV, AAAI
Was recognized as a top reviewer for NeurIPS 2019
Was recognized as an outstanding reviewer for CVPR 2019
Dipan K. Pal, Sreena Nallamothu and Marios Savvides, Towards a Hypothesis on Visual Transformation based Self-Supervision, BMVC 2020
Ran Tao, Dipan K. Pal and Marios Savvides, Weight Generation from Samples for Few Shot Learning
Dipan K. Pal, Akshay Chawla and Marios Savvides, Learning Non-Parametric Invariances from Data with Permanent Random Connectomes, BMVC 2020, NeurIPS SVRHM 2019, poster
Raied Aljadaany, Dipan K. Pal and Marios Savvides, Proximal Splitting Networks for Image Restoration, ICIAR 2019 (oral)
Raied Aljadaany, Dipan K. Pal and Marios Savvides, Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution, CVPR 2019, poster
Dipan K. Pal and Marios Savvides, Non-Parametric Transformation Networks for learning General Invariances from Data, AAAI 2019 (spotlight oral, overall acceptance rate of 16.2%), poster
Dipan K. Pal*, Sekhar Bhagavatula*, Yutong Zheng, Ran Tao and Marios Savvides, Is Pose Really Solved? A Frontalization Approach for Robust Off-Angle Face Matching, WACV 2019 (* indicates equal contribution)
Yutong Zheng, Dipan K. Pal and Marios Savvides, Ring loss: Convex Feature Normalization for Face Recognition, CVPR 2018, poster
Dipan K. Pal and Marios Savvides, Copernican loss: Learning a Discriminative Cosine Embedding
Dipan K. Pal and Marios Savvides, How ConvNets model Non-linear Invariances, arXiv 2017
Dipan K. Pal, Ashwin A. Kannan*, Gautam Arakalgud* and Marios Savvides, Max-margin Invariant Features: Unitary-Group Invariant Kernels from Transformed Unlabeled Data, NIPS 2017 (* indicates equal contribution), poster
Dipan K. Pal, Vishnu N. Boddeti and Marios Savvides, Emergence of Selective Invariance for Object Categorization through Adaptive Pooling, arXiv 2017
Dipan K. Pal and Marios Savvides, Unitary-Group Invariant Kernels and Features from Transformed Unlabeled Data, arXiv 2016
Dipan K. Pal and Ole Mengshoel, Stochastic CoSaMP: Randomizing Greedy Pursuit for Sparse Signal Recovery, ECML-PKDD, 2016. Supplementary Material
Dipan K. Pal, Felix Juefei-Xu and Marios Savvides, Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation, CVPR 2016 (spotlight oral presentation), poster
Felix Juefei-Xu, Dipan K. Pal and Marios Savvides, Hallucinating the Full Face from the Periocular Region via Dimensionally Weighted K-SVD, CVPRW Biometrics, 2014
Dipan K Pal, S. S. Tripathy, Viresh Ranjan, Avinash Das, Robust Content Based Image Retrieval system using Hierarchical Temporal Memory, ICECT, 2012 (only paper proceedings published)
Dipan K Pal, Evaluation of Gabor Filter enhanced Hierarchical Temporal Memories in image classification applications, IEEE ICCIC, 2011 (only paper proceedings published)
Dipan K Pal, Biometric identification using Hierarchical Temporal Memory with face recognition as a case study, IEEE ICCIC, 2011 (only paper proceedings published)
Was recognized as a top reviewer for NeurIPS 2019
Was recognized as an outstanding reviewer for CVPR 2019
Publications (major contribution)
Dipan K. Pal, Sreena Nallamothu and Marios Savvides, Towards a Hypothesis on Visual Transformation based Self-Supervision, BMVC 2020
Ran Tao, Dipan K. Pal and Marios Savvides, Weight Generation from Samples for Few Shot Learning
Dipan K. Pal, Akshay Chawla and Marios Savvides, Learning Non-Parametric Invariances from Data with Permanent Random Connectomes, BMVC 2020, NeurIPS SVRHM 2019, poster
Raied Aljadaany, Dipan K. Pal and Marios Savvides, Proximal Splitting Networks for Image Restoration, ICIAR 2019 (oral)
Raied Aljadaany, Dipan K. Pal and Marios Savvides, Douglas-Rachford Networks: Learning Both the Image Prior and Data Fidelity Terms for Blind Image Deconvolution, CVPR 2019, poster
Dipan K. Pal and Marios Savvides, Non-Parametric Transformation Networks for learning General Invariances from Data, AAAI 2019 (spotlight oral, overall acceptance rate of 16.2%), poster
Dipan K. Pal*, Sekhar Bhagavatula*, Yutong Zheng, Ran Tao and Marios Savvides, Is Pose Really Solved? A Frontalization Approach for Robust Off-Angle Face Matching, WACV 2019 (* indicates equal contribution)
Yutong Zheng, Dipan K. Pal and Marios Savvides, Ring loss: Convex Feature Normalization for Face Recognition, CVPR 2018, poster
Dipan K. Pal and Marios Savvides, Copernican loss: Learning a Discriminative Cosine Embedding
Dipan K. Pal and Marios Savvides, How ConvNets model Non-linear Invariances, arXiv 2017
Dipan K. Pal, Ashwin A. Kannan*, Gautam Arakalgud* and Marios Savvides, Max-margin Invariant Features: Unitary-Group Invariant Kernels from Transformed Unlabeled Data, NIPS 2017 (* indicates equal contribution), poster
Dipan K. Pal, Vishnu N. Boddeti and Marios Savvides, Emergence of Selective Invariance for Object Categorization through Adaptive Pooling, arXiv 2017
Dipan K. Pal and Marios Savvides, Unitary-Group Invariant Kernels and Features from Transformed Unlabeled Data, arXiv 2016
Dipan K. Pal and Ole Mengshoel, Stochastic CoSaMP: Randomizing Greedy Pursuit for Sparse Signal Recovery, ECML-PKDD, 2016. Supplementary Material
Dipan K. Pal, Felix Juefei-Xu and Marios Savvides, Discriminative Invariant Kernel Features: A Bells-and-Whistles-Free Approach to Unsupervised Face Recognition and Pose Estimation, CVPR 2016 (spotlight oral presentation), poster
Felix Juefei-Xu, Dipan K. Pal and Marios Savvides, Hallucinating the Full Face from the Periocular Region via Dimensionally Weighted K-SVD, CVPRW Biometrics, 2014
Dipan K Pal, S. S. Tripathy, Viresh Ranjan, Avinash Das, Robust Content Based Image Retrieval system using Hierarchical Temporal Memory, ICECT, 2012 (only paper proceedings published)
Dipan K Pal, Evaluation of Gabor Filter enhanced Hierarchical Temporal Memories in image classification applications, IEEE ICCIC, 2011 (only paper proceedings published)
Dipan K Pal, Biometric identification using Hierarchical Temporal Memory with face recognition as a case study, IEEE ICCIC, 2011 (only paper proceedings published)
Other Publications
Pokkalla Harsha Vardhan, Kunal Sekhri, Dipan K. Pal and Marios Savvides, Class Correlation affects Single Object Localization using Pre-trained ConvNets, arXiv 2017
Shreyas Venugopalan, Dipan K. Pal, Marios Savvides, Exploiting Sparsity in Local Iris Texture Representation: An Iris Spoofing Paradigm (under review)
Ngan Le, Chi Nhan Duong, Ligong Han, Khoa Luu, Marios Savvides, Dipan K. Pal, Deep Contextual Recurrent Residual Networks for Scene Labeling, arXiv 2017
Felix Juefei-Xu, Dipan K. Pal and Marios Savvides, NIR-VIS Heterogeneous Face Recognition via Cross-Spectral Joint Dictionary Learning and Reconstruction, CVPRW Perception Beyond the Visual Spectrum Workshop, 2015
Keshav Seshadri, Felix Juefei-Xu, Dipan K. Pal, Marios Savvides and C.P. Thor, Driver Cell Phone Usage Detection on Strategic Highway Research Program (SHRP2) Face View Videos, CVPRW Workshop on Computer Vision in Vehicle Technology, 2015
Felix Juefei-Xu, Dipan K. Pal, Karanhaar Singh, and Marios Savvides, A Preliminary Investigation on the Sensitivity of COTS Face Recognition Systems to Forensic Analyst-style Face Processing for Occlusions, CVPRW Biometrics, 2015
Niv Zehngut, Felix Juefei-Xu, Rishabh Bardia, Dipan K. Pal, Chandrasekhar Bhagavatula, and Marios Savvides, Investigating the Feasibility of Image-Based Nose Biometrics, ICIP, 2015
Jun Shi, Ole Mengshoel, Dipan K. Pal, Feedback control for multi-modal optimization using genetic algorithms, GECCO, 2014
Shreyas Venugopalan, Dipan K. Pal, Marios Savvides, Exploiting Sparsity in Local Iris Texture Representation: An Iris Spoofing Paradigm (under review)
Ngan Le, Chi Nhan Duong, Ligong Han, Khoa Luu, Marios Savvides, Dipan K. Pal, Deep Contextual Recurrent Residual Networks for Scene Labeling, arXiv 2017
Felix Juefei-Xu, Dipan K. Pal and Marios Savvides, NIR-VIS Heterogeneous Face Recognition via Cross-Spectral Joint Dictionary Learning and Reconstruction, CVPRW Perception Beyond the Visual Spectrum Workshop, 2015
Keshav Seshadri, Felix Juefei-Xu, Dipan K. Pal, Marios Savvides and C.P. Thor, Driver Cell Phone Usage Detection on Strategic Highway Research Program (SHRP2) Face View Videos, CVPRW Workshop on Computer Vision in Vehicle Technology, 2015
Felix Juefei-Xu, Dipan K. Pal, Karanhaar Singh, and Marios Savvides, A Preliminary Investigation on the Sensitivity of COTS Face Recognition Systems to Forensic Analyst-style Face Processing for Occlusions, CVPRW Biometrics, 2015
Niv Zehngut, Felix Juefei-Xu, Rishabh Bardia, Dipan K. Pal, Chandrasekhar Bhagavatula, and Marios Savvides, Investigating the Feasibility of Image-Based Nose Biometrics, ICIP, 2015
Jun Shi, Ole Mengshoel, Dipan K. Pal, Feedback control for multi-modal optimization using genetic algorithms, GECCO, 2014
Patents
Felix Juefei-Xu, Dipan K. Pal, and Marios Savvides, “Methods and Software for Hallucinating Facial Features by Prioritizing Reconstruction Errors”, U.S. Provisional Patent Application Serial No. 61/998,043, June 17, 2014.
Curriculum Vitae
Please download a copy of my CV from here.