most citedAIM 2020 Challenge on Rendering Realistic Bokeh

6 citations · 6 across the 3 of their papers we have counts for

collaborators

9 papers

eess.IV2021

Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report

Andrey Ignatov, Grigory Malivenko, Radu Timofte +28

Camera scene detection is among the most popular computer vision problem on smartphones. While many custom solutions were developed for this task by phone vendors, none of the desi…

cs.CV2021

Stacked Deep Multi-Scale Hierarchical Network for Fast Bokeh Effect Rendering from a Single Image

Saikat Dutta, Sourya Dipta Das, Nisarg A. Shah +1

The Bokeh Effect is one of the most desirable effects in photography for rendering artistic and aesthetic photos. Usually, it requires a DSLR camera with different aperture and shu…

eess.IV2021

Efficient Space-time Video Super Resolution using Low-Resolution Flow and Mask Upsampling

Saikat Dutta, Nisarg A. Shah, Anurag Mittal

This paper explores an efficient solution for Space-time Super-Resolution, aiming to generate High-resolution Slow-motion videos from Low Resolution and Low Frame rate videos. A si…

cs.CV2021

DSRN: an Efficient Deep Network for Image Relighting

Sourya Dipta Das, Nisarg A. Shah, Saikat Dutta +1

Custom and natural lighting conditions can be emulated in images of the scene during post-editing. Extraordinary capabilities of the deep learning framework can be utilized for suc…

cs.CL2021

A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection

Sourya Dipta Das, Ayan Basak, Saikat Dutta

The significance of social media has increased manifold in the past few decades as it helps people from even the most remote corners of the world stay connected. With the COVID-19…

eess.IV20206 cited

AIM 2020 Challenge on Rendering Realistic Bokeh

Andrey Ignatov, Radu Timofte, Ming Qian +32

This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. The participating teams were solvin…