Dipan Pal


I am an ECE PhD student at Carnegie Mellon University. My current interests lie broadly in the intersection of perception, computer vision and deep learning. I work with Prof. Marios Savvides, at the CyLab Biometrics Center. I also occasionally collaborate 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 in high dimensional kernel spaces are very useful. Currently, I am investigating the invariance and equivariance properties of convolutional architectures and in doing so am developing a new class of convolutional architectures called Non Parametric Transformation Networks. Another line of research is to investigate the motivation and benefits of permanent random connections in convolutional architectures. This presents a classes of networks called Randomly Structured Convolutional Networks, which are the first networks to have completely random and permanent connections throughout training and testing. Also, some of my work is focused towards building state-of-the-art face recognition systems that are robust to transformations such as pose. Other projects in and around deep learning include developing L0 sparse approximation algorithms combined with deep learning, single image super resolution and blind deblurring and defocusing. Applications of the former include compression and unsupervised learning. I have also developed a few loss functions towards the traditional large scale supervised learning problem. Current projects also involve aspects of multi-task learning using a single Transformation Network, investigating more general aspects of reasoning.

In the works

Dipan K. Pal, Raied Aljadaany and Marios Savvides, Deep L0 Sparse Approximation

In the pipeline

Dipan K. Pal and Marios Savvides, Learning Non-Parametric Invariances from Data with Permanent Random Connectomes

Publications (major contribution)

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

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%)

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

Dipan K. Pal and Marios Savvides, Copernican loss: Learning a Discriminative Cosine Embedding, preprint

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)

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)

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


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.