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20212024
most citedAIM 2024 Sparse Neural Rendering Challenge: Methods and Results

8 citations · 8 across the 6 of their papers we have counts for

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6 papers

cs.CV20248 cited

AIM 2024 Sparse Neural Rendering Challenge: Methods and Results

Michal Nazarczuk, Sibi Catley-Chandar, Thomas Tanay +27

This paper reviews the challenge on Sparse Neural Rendering that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. This manuscript…

cs.CV2024

Spatially-Attentive Patch-Hierarchical Network with Adaptive Sampling for Motion Deblurring

Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan

This paper tackles the problem of motion deblurring of dynamic scenes. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform mo…

eess.IV2022

Image Restoration using Feature-guidance

Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan

Image restoration is the task of recovering a clean image from a degraded version. In most cases, the degradation is spatially varying, and it requires the restoration network to b…

cs.CV2022

Adaptive Image Inpainting

Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan

Image inpainting methods have shown significant improvements by using deep neural networks recently. However, many of these techniques often create distorted structures or blurry t…

eess.IV2022

Adaptive Single Image Deblurring

Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan

This paper tackles the problem of dynamic scene deblurring. Although end-to-end fully convolutional designs have recently advanced the state-of-the-art in non-uniform motion deblur…

cs.CV2021

Mitigating Channel-wise Noise for Single Image Super Resolution

Srimanta Mandal, Kuldeep Purohit, A. N. Rajagopalan

In practice, images can contain different amounts of noise for different color channels, which is not acknowledged by existing super-resolution approaches. In this paper, we propos…