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- XVFI: eXtreme Video Frame Interpolation227
An extreme VFI network is proposed, called XVFI-Net, that first handles the VFI for 4K videos with large motion that performs comparably on the previous lower resolution benchmark dataset, which shows a robustness of the algorithm.
- A VOP generation tool: automatic segmentation of moving objects in image sequences based on spatio-temporal information179
An image segmentation method for separating moving objects from the background in image sequences using a combination of the spatial and temporal segmentation masks produces VOPs faithfully.
- 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.
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- NTIRE 2020 Challenge on NonHomogeneous Dehazing125
This paper reviews the NTIRE 2020 Challenge on Non-Homogeneous Dehazing of images (restoration of rich details in hazy image) and proposed solutions gauge the state-of-the-art in image dehazing.
- Deep SR-ITM: Joint Learning of Super-Resolution and Inverse Tone-Mapping for 4K UHD HDR Applications117
This paper proposes a joint super-resolution (SR) and inverse tone-mapping (ITM) framework, called Deep SR-ITM, which learns the direct mapping from LR SDR video to their HR HDR version, and shows good subjective quality with increased contrast and details, outperforming the previous joint SR and ITM method.
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- JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video93
This paper takes a divide-and-conquer approach in designing a novel GAN-based joint SR-ITM network, called JSI-GAN, which is composed of three task-specific subnets: an image reconstruction subnet, a detail restoration subnet and a local contrast enhancement (LCE) subnet.
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- KOALAnet: Blind Super-Resolution using Kernel-Oriented Adaptive Local Adjustment88
The proposed KOALAnet produces the most natural results for artistic photographs with intentional blur, which are not over-sharpened, by effectively handling images mixed with in-focus and out-of-focus areas.
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- FISR: Deep Joint Frame Interpolation and Super-Resolution with a Multi-Scale Temporal Loss75
A novel training scheme with a multi-scale temporal loss that imposes temporal regularization on the input video sequence, which can be applied to any general video-related task is proposed and analyzed in depth with extensive experiments.
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- Moving object segmentation in video sequences by user interaction and automatic object tracking64
A user-assisted video segmentation method for separating moving objects from the background in video sequences that exhibits a consistent and faithful segmentation performance for various types of video sequences is addressed.
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 2026-10-13. 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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