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Found 7 papers, 6 papers with code
UniVS: Unified and Universal Video Segmentation with Prompts as Queries
Despite the recent advances in unified image segmentation (IS), developing a unified video segmentation (VS) model remains a challenge.
Ranked #2 on
Video Semantic Segmentation
on VSPW
(using extra training data)
Referring Expression Segmentation
Referring Video Object Segmentation
+6
Generalized Large-Scale Data Condensation via Various Backbone and Statistical Matching
We call this perspective "generalized matching" and propose Generalized Various Backbone and Statistical Matching (G-VBSM) in this work, which aims to create a synthetic dataset with densities, ensuring consistency with the complete dataset across various backbones, layers, and statistics.
Human Guided Ground-truth Generation for Realistic Image Super-resolution
A human guided GT image dataset with both positive and negative samples is then constructed, and a loss function is proposed to train the Real-ISR models.
Spatial-Frequency Attention for Image Denoising
In this paper, we propose the spatial-frequency attention network (SFANet) to enhance the network's ability in exploiting long-range dependency.
Joint HDR Denoising and Fusion: A Real-World Mobile HDR Image Dataset
In this work, we develop, for the first time to our best knowledge, an HDR image dataset by using mobile phone cameras, namely Mobile-HDR dataset.
Efficient Long-Range Attention Network for Image Super-resolution
A highly efficient long-range attention block (ELAB) is then built by simply cascading two shift-conv with a GMSA module, which is further accelerated by using a shared attention mechanism.
Ranked #11 on
Image Super-Resolution
on Manga109 - 4x upscaling
Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report
Image super-resolution is one of the most popular computer vision problems with many important applications to mobile devices.
