Rajeev Yasarla

PhD Student, ECE Dept., Whiting School of Engineering, Johns Hopkins University

I recently graduated with a Ph.D. degree in Electrical engineering from Electrical and Computer Engineering Dept. at Johns Hopkins University, Whiting School of Engineering. I was advised by Vishal M. Patel. Prior to joining Johns Hopkins, I graduated from IIT Madras with a bachelor's and master's degree.

My research focus lies in computer vision and machine learning, specifically focusing on semi-, un-, and self-supervised deep learning methods for adverse weather removal tasks( rain, fog, snow), image enhancement, and image-to-image translation for large-scale vision, and salient object detection.

I interned at AIBEE in the summer of 2021 where I worked on self-supervised salient object detection. I interned at Microsoft in the summer of 2020 where I worked on face enhancement.


Email / CV / Google Scholar / Linkedin / Github

News

  • July 2022 - one paper accepted at ECCV 2022.

  • May 2022 - one paper was accepted for oral presentation at EUSIPCO 2022.

  • April 2022 - one journal paper was published in IEEE TBIOM 2020.

  • March 2022 - one paper was accepted for oral presentation at ICPR 2022.

  • March 2022 - one paper was accepted at CVPR 2022.

  • September 2021 - Best Paper Award IEEE ICIP 2021.

  • July 2021 - one journal paper was published in IEEE TIP 2020.

  • July 2020 - two papers accepted at ECCV 2020.

  • April 2020 - one journal paper was published in IEEE TIP 2020.

  • Feb 2020 - one paper accepted for oral presentation at CVPR 2020.

  • Feb 2020 - one journal paper was published in IEEE TIP 2020.

  • Oct 2019 - Awarded student grant from ICCV PCO for attending ICCV 2019.

  • July 2019 - one paper was accepted at ICCV 2019, Seoul.

  • Feb 2019 - one paper accepted at CVPR 2019, Long Beach.

Teaching

  • Teaching Assistant: Introduction to Digital Signal Processing EN.520.344, Fall 2021, ECE Dept., WSE, Johns Hopkins University.

  • Teaching Assistant: Introduction to Digital Signal Processing EN.520.344, Fall 2020, ECE Dept., WSE, Johns Hopkins University.

  • Teaching Assistant: Introduction to Digital Signal Processing EN.520.344, Fall 2019, ECE Dept., WSE, Johns Hopkins University.

  • Teaching Assistant: Introduction to Data Structures and Algorithms EE4371, Spring 2016, Dept. of Electrical Eng., IIT Madras.

  • Teaching Assistant: Basic Electrical Engineering EE1100, Fall 2015, Dept. of Electrical Eng., IIT Madras.

Selected Publications

Syn2Real Transfer Learning for Image Deraining using Gaussian Processes

Rajeev Yasarla*, Vishwanath Sindagi*, Vishal M. Patel; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.

Confidence Measure Guided Single Image De-raining

Rajeev Yasarla, Vishal M. Patel; IEEE Transactions on Image Processing, 2020.

Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks

Rajeev Yasarla, Federico Perazzi, Vishal M. Patel; IEEE Transactions on Image Processing, 2020.

Uncertainty Guided Multi-Scale Residual Learning-Using a Cycle Spinning CNN for Single Image De-Raining

Rajeev Yasarla, Vishal M. Patel; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, Long Beach .

All Publications

Conference Papers

  1. ART-SS: An Adaptive Rejection Technique for Semi-Supervised restoration for adverse weather-affected images, Rajeev Yasarla, Carey E. Priebe and Vishal M. Patel, ECCV 2022.

  2. Unsupervised Restoration of Weather-affected Images using Deep Gaussian Process-based CycleGAN, Rajeev Yasarla, Vishwanath A. Sindagi and Vishal M. Patel, ICPR 2022.

  3. TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions, J.M.J. Valanarasu, Rajeev Yasarla, and Vishal M. Patel, IEEE/CVF CVPR 2022.

  4. Network Architecture Search for Face Enhancement, Rajeev Yasarla, Hamid Reza Vaezi Joze and Vishal M. Patel, IEEE EUSIPCO 2022.

  5. Learning to Restore Images Degraded by Atmospheric Turbulence Using Uncertainty, Rajeev Yasarla and Vishal M. Patel, IEEE ICIP 2021. (Best paper award)

  6. Syn2Real Transfer Learning for Image Deraining using Gaussian Processes, Rajeev Yasarla, Vishwanath A. Sindagi, and Vishal M. Patel, IEEE/CVF CVPR 2020. (oral presentation)

  7. Prior-based Domain Adaptive Object Detection for Hazy and Rainy Conditions, Vishwanath A. Sindagi*, Poojan Oza*, Rajeev Yasarla and Vishal M. Patel, ECCV 2020.

  8. Learning to Count in the Crowd from Limited Labeled Data, Vishwanath A. Sindagi, Rajeev Yasarla, Deepak Sam Babu, R. Venkatesh Babu, and Vishal M. Patel, ECCV2020.

  9. Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method, Vishwanath A. Sindagi, Rajeev Yasarla, and Vishal M. Patel, IEEE ICCV 2019.

  10. Uncertainty Guided Multi-Scale Residual Learning-Using a Cycle Spinning CNN for Single Image De-Raining, Rajeev Yasarla, and Vishal M. Patel, IEEE/CVF CVPR 2019.

Journal Papers

  1. CNN-based Restoration of a Single Face Image Degraded by Atmospheric Turbulence, Rajeev Yasarla, and Vishal M. Patel, IEEE TBIOM 2022.

  2. Semi-Supervised Image Deraining Using Gaussian Processes, Rajeev Yasarla, Vishwanath A. Sindagi, and Vishal M. Patel, IEEE TIP 2021.

  3. Confidence Measure Guided Single Image De-Raining, Rajeev Yasarla, and Vishal M. Patel, IEEE TIP 2020.

  4. Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks, Rajeev Yasarla, Federico Perazzi, and Vishal M. Patel, IEEE TIP 2020.

  5. Exploring Overcomplete Representations for Single Image Deraining Using CNNs, Rajeev Yasarla, J.M.J. Valanarasu, and Vishal M. Patel, IEEE JSTSP 2020.

  6. JHU-CROWD++: Large-Scale Crowd Count- ing Dataset and A Benchmark Method, Vishwanath A. Sindagi, Rajeev Yasarla, and Vishal M. Patel, IEEE TPAMI 2020.

  7. Learning to Segment Brain Anatomy From 2D Ultrasound With Less Data, J.M.J. Valanarasu, Rajeev Yasarla, and Vishal M. Patel, IEEE JSTSP 2020.