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20162022
most citedLP-3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networks

5 citations · 12 across the 18 of their papers we have counts for

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Showing 2019Show all

9 papers · 1 filter

cs.CV2019

FHDR: HDR Image Reconstruction from a Single LDR Image using Feedback Network

Zeeshan Khan, Mukul Khanna, Shanmuganathan Raman

High dynamic range (HDR) image generation from a single exposure low dynamic range (LDR) image has been made possible due to the recent advances in Deep Learning. Various feed-forw…

cs.CV2019

Simultaneous Detection and Removal of Dynamic Objects in Multi-view Images

Gagan Kanojia, Shanmuganathan Raman

Consider a set of images of a scene consisting of moving objects captured using a hand-held camera. In this work, we propose an algorithm which takes this set of multi-view images…

eess.IV2019

DCIL: Deep Contextual Internal Learning for Image Restoration and Image Retargeting

Indra Deep Mastan, Shanmuganathan Raman

Recently, there is a vast interest in developing methods which are independent of the training samples such as deep image prior, zero-shot learning, and internal learning. The meth…

cs.CV2019

DeepPFCN: Deep Parallel Feature Consensus Network For Person Re-Identification

Shubham Kumar Singh, Krishna P Miyapuram, Shanmuganathan Raman

Person re-identification aims to associate images of the same person over multiple non-overlapping camera views at different times. Depending on the human operator, manual re-ident…

cs.CV2019

Exploring Temporal Differences in 3D Convolutional Neural Networks

Gagan Kanojia, Sudhakar Kumawat, Shanmuganathan Raman

Traditional 3D convolutions are computationally expensive, memory intensive, and due to large number of parameters, they often tend to overfit. On the other hand, 2D CNNs are less…

eess.IV2019

Multi-level Encoder-Decoder Architectures for Image Restoration

Indra Deep Mastan, Shanmuganathan Raman

Many real-world solutions for image restoration are learning-free and based on handcrafted image priors such as self-similarity. Recently, deep-learning methods that use training d…