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- Subhasis ChaudhuriSuggested from co-authorship
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Works245 from public data
- 647
- Spatially-Attentive Patch-Hierarchical Network for Adaptive Motion Deblurring336
This work proposes an efficient pixel adaptive and feature attentive design for handling large blur variations across different spatial locations and proposes an effective content-aware global-local filtering module that significantly improves performance by considering not only global dependencies but also by dynamically exploiting neighboring pixel information.
- Depth From Defocus: A Real Aperture Imaging Approach265
A Partial Derivatives of Various Quantities in CRB, a MAP-MRF approach to Depth Recovery and Restoration using MRF Models.
- Gait Analysis for Human Identification256
The dynamic time-warping (DTW) approach is used for matching so that non-linear time normalization may be used to deal with the naturally-occuring changes in walking speed.
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- Off-line signature verification using DTW209
A signature verification system based on Dynamic Time Warping (DTW) that works by extracting the vertical projection feature from signature images and by comparing reference and probe feature templates using elastic matching is proposed.
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- Spatially-Adaptive Image Restoration using Distortion-Guided Networks166
The key idea is to exploit the non-uniformity of heavy degradations in spatial-domain and suitably embed this knowledge within distortion-guided modules performing sparse normalization, feature extraction and attention.
- PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report161
This paper reviews the first challenge on efficient perceptual image enhancement with the focus on deploying deep learning models on smartphones and proposes solutions that significantly improved baseline results defining the state-of-the-art for image enhancement on smartphones.
- Region-Adaptive Dense Network for Efficient Motion Deblurring148
This paper presents a new architecture composed of region adaptive dense deformable modules that implicitly discover the spatially varying shifts responsible for non-uniform blur in the input image and learn to modulate the filters, enabling almost real-time deblurring.
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- An MRF model-based approach to simultaneous recovery of depth and restoration from defocused images106
The performance of the proposed MAP-Markov random field based scheme for recovering the depth and the focused image of a scene from two defocused images is found to be better than that of the existing window-based depth from defocus technique.
- AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results101
The AIM 2020 challenge on efficient single image super-resolution was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images with focus on the proposed solutions and results.
- Bringing Alive Blurred Moments92
This work first learns motion representation from sharp videos in an unsupervised manner through training of a convolutional recurrent video autoencoder network that performs a surrogate task of video reconstruction that outperforms competing methods across all factors: accuracy, speed, and compactness.
- Human Face Detection in Cluttered Color Images Using Skin Color, Edge Information.80
A fast algorithm for detecting human faces in color images using color histogram for skin (in the HSV space) in conjunction with edge information to quickly locate faces in a given image is proposed.
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- A variational approach to recovering depth from defocused images67
A smoothness constraint is imposed on the estimates of the blur parameter, and a variational approach to the DFD problem is developed using the space-frequency representation (SFR) framework.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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