Rajeev Yasarla | DeepAI

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Vishal M. Patel
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Jeya Maria Jose Valanarasu
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Pengfei Guo
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Amir Sadeghian
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∙ 07/26/2023

MAMo: Leveraging Memory and Attention for Monocular Video Depth Estimation

We propose MAMo, a novel memory and attention frame-work for monocular v...

0 Rajeev Yasarla, et al. ∙

∙ 09/20/2022

NBD-GAP: Non-Blind Image Deblurring Without Clean Target Images

In recent years, deep neural network-based restoration methods have achi...

6 Nithin Gopalakrishnan Nair, et al. ∙

∙ 07/07/2022

Learning to restore images degraded by atmospheric turbulence using uncertainty

Atmospheric turbulence can significantly degrade the quality of images a...

0 Rajeev Yasarla, et al. ∙

∙ 04/23/2022

Unsupervised Restoration of Weather-affected Images using Deep Gaussian Process-based CycleGAN

Existing approaches for restoring weather-degraded images follow a fully...

0 Rajeev Yasarla, et al. ∙

∙ 03/17/2022

ART-SS: An Adaptive Rejection Technique for Semi-Supervised restoration for adverse weather-affected images

In recent years, convolutional neural network-based single image adverse...

0 Rajeev Yasarla, et al. ∙

∙ 03/09/2022

3SD: Self-Supervised Saliency Detection With No Labels

We present a conceptually simple self-supervised method for saliency det...

0 Rajeev Yasarla, et al. ∙

∙ 11/29/2021

TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditions

Removing adverse weather conditions like rain, fog, and snow from images...

8 Jeya Maria Jose Valanarasu, et al. ∙

∙ 05/13/2021

Network Architecture Search for Face Enhancement

Various factors such as ambient lighting conditions, noise, motion blur,...

0 Rajeev Yasarla, et al. ∙

∙ 10/20/2020

Exploring Overcomplete Representations for Single Image Deraining using CNNs

Removal of rain streaks from a single image is an extremely challenging ...

5 Rajeev Yasarla, et al. ∙

∙ 09/25/2020

Semi-Supervised Image Deraining using Gaussian Processes

Recent CNN-based methods for image deraining have achieved excellent per...

0 Rajeev Yasarla, et al. ∙

∙ 08/06/2020

Confidence-guided Lesion Mask-based Simultaneous Synthesis of Anatomic and Molecular MR Images in Patients with Post-treatment Malignant Gliomas

Data-driven automatic approaches have demonstrated their great potential...

5 Pengfei Guo, et al. ∙

∙ 07/16/2020

Learning to Restore a Single Face Image Degraded by Atmospheric Turbulence using CNNs

Atmospheric turbulence significantly affects imaging systems which use l...

4 Rajeev Yasarla, et al. ∙

∙ 07/07/2020

Learning to Count in the Crowd from Limited Labeled Data

Recent crowd counting approaches have achieved excellent performance. ho...

6 Vishwanath A. Sindagi, et al. ∙

∙ 04/07/2020

JHU-CROWD++: Large-Scale Crowd Counting Dataset and A Benchmark Method

Due to its variety of applications in the real-world, the task of single...

3 Vishwanath A. Sindagi, et al. ∙

∙ 12/18/2019

Learning to Segment Brain Anatomy from 2D Ultrasound with Less Data

Automatic segmentation of anatomical landmarks from ultrasound (US) play...

15 Jeya Maria Jose V., et al. ∙

∙ 11/29/2019

Prior-based Domain Adaptive Object Detection for Adverse Weather Conditions

Adverse weather conditions such as rain and haze corrupt the quality of ...

11 Vishwanath A. Sindagi, et al. ∙

∙ 10/28/2019

Pushing the Frontiers of Unconstrained Crowd Counting: New Dataset and Benchmark Method

In this work, we propose a novel crowd counting network that progressive...

21 Vishwanath A. Sindagi, et al. ∙

∙ 09/10/2019

Confidence Measure Guided Single Image De-raining

Single image de-raining is an extremely challenging problem since the ra...

1 Rajeev Yasarla, et al. ∙

∙ 07/30/2019

Deblurring Face Images using Uncertainty Guided Multi-Stream Semantic Networks

We propose a novel multi-stream architecture and training methodology th...

4 Rajeev Yasarla, et al. ∙

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