Search Results for author: Sudeep Sarkar

Found 17 papers, 6 papers with code

Learning Actor-centered Representations for Action Localization in Streaming Videos using Predictive Learning

no code implementations29 Apr 2021 Sathyanarayanan N. Aakur, Sudeep Sarkar

Finally, we show that the proposed model can generalize to out-of-domain data without significant loss in performance without any finetuning for both the recognition and localization tasks.

Action Localization

Measuring economic activity from space: a case study using flying airplanes and COVID-19

1 code implementation21 Apr 2021 Mauricio Pamplona Segundo, Allan Pinto, Rodrigo Minetto, Ricardo da Silva Torres, Sudeep Sarkar

This work introduces a novel solution to measure economic activity through remote sensing for a wide range of spatial areas.

Spatio-Temporal Event Segmentation and Localization for Wildlife Extended Videos

no code implementations5 May 2020 Ramy Mounir, Roman Gula, Jörn Theuerkauf, Sudeep Sarkar

We present a self-supervised perceptual prediction framework capable of temporal event segmentation by building stable representations of objects over time and demonstrate it on long videos, spanning several days.

Action Detection Activity Detection +2

A Quotient Space Formulation for Generative Statistical Analysis of Graphical Data

1 code implementation30 Sep 2019 Xiaoyang Guo, Anuj Srivastava, Sudeep Sarkar

Complex analyses involving multiple, dependent random quantities often lead to graphical models - a set of nodes denoting variables of interest, and corresponding edges denoting statistical interactions between nodes.

Dimensionality Reduction

Abductive Reasoning as Self-Supervision for Common Sense Question Answering

no code implementations6 Sep 2019 Sathyanarayanan N. Aakur, Sudeep Sarkar

We find that large amounts of training data are necessary, both for pre-training as well as fine-tuning to a task, for the models to perform well on the designated task.

Common Sense Reasoning Domain Adaptation +1

The Unconstrained Ear Recognition Challenge 2019 - ArXiv Version With Appendix

no code implementations11 Mar 2019 Žiga Emeršič, Aruna Kumar S. V., B. S. Harish, Weronika Gutfeter, Jalil Nourmohammadi Khiarak, Andrzej Pacut, Earnest Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar, Hyeonjung Park, Gi Pyo Nam, Ig-Jae Kim, Sagar G. Sangodkar, Ümit Kaçar, Murvet Kirci, Li Yuan, Jishou Yuan, Haonan Zhao, Fei Lu, Junying Mao, Xiaoshuang Zhang, Dogucan Yaman, Fevziye Irem Eyiokur, Kadir Bulut Özler, Hazim Kemal Ekenel, Debbrota Paul Chowdhury, Sambit Bakshi, Pankaj K. Sa, Banshidhar Majhi, Peter Peer, Vitomir Štruc

The goal of the challenge is to assess the performance of existing ear recognition techniques on a challenging large-scale ear dataset and to analyze performance of the technology from various viewpoints, such as generalization abilities to unseen data characteristics, sensitivity to rotations, occlusions and image resolution and performance bias on sub-groups of subjects, selected based on demographic criteria, i. e. gender and ethnicity.

Person Recognition

A Perceptual Prediction Framework for Self Supervised Event Segmentation

1 code implementation CVPR 2019 Sathyanarayanan N. Aakur, Sudeep Sarkar

We also show that the proposed approach is able to learn highly discriminative features that help improve action recognition when used in a representation learning paradigm.

Action Recognition Event Segmentation +1

Resource-Constrained Simultaneous Detection and Labeling of Objects in High-Resolution Satellite Images

no code implementations23 Oct 2018 Gilbert Rotich, Rodrigo Minetto, Sudeep Sarkar

We describe a strategy for detection and classification of man-made objects in large high-resolution satellite photos under computational resource constraints.

A method to Suppress Facial Expression in Posed and Spontaneous Videos

no code implementations4 Oct 2018 Ghada Zamzmi, Gabriel Ruiz, Matthew Shreve, Dmitry Goldgof, Rangachar Kasturi, Sudeep Sarkar

We address the problem of suppressing facial expressions in videos because expressions can hinder the retrieval of important information in applications such as face recognition.

Face Recognition

Hydra: an Ensemble of Convolutional Neural Networks for Geospatial Land Classification

1 code implementation10 Feb 2018 Rodrigo Minetto, Mauricio Pamplona Segundo, Sudeep Sarkar

With this framework, we were able to reduce the training time while maintaining the classification performance of the ensemble.

General Classification

Employing Fusion of Learned and Handcrafted Features for Unconstrained Ear Recognition

1 code implementation20 Oct 2017 Earnest E. Hansley, Mauricio Pamplona Segundo, Sudeep Sarkar

We used the results generated to perform a geometric image normalization that boosted the performance of all evaluated descriptors.

Going Deeper with Semantics: Video Activity Interpretation using Semantic Contextualization

no code implementations11 Aug 2017 Sathyanarayanan N. Aakur, Fillipe DM de Souza, Sudeep Sarkar

Through extensive experiments, we show that the use of commonsense knowledge from ConceptNet allows the proposed approach to handle various challenges such as training data imbalance, weak features, and complex semantic relationships and visual scenes.

Temporally Coherent Interpretations for Long Videos Using Pattern Theory

no code implementations CVPR 2015 Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su

Graph-theoretical methods have successfully provided semantic and structural interpretations of images and videos.

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