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Found 8 papers, 4 papers with code
PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild
In this paper, we propose a VQA method named PTM-VQA, which leverages PreTrained Models to transfer knowledge from models pretrained on various pre-tasks, enabling benefits for VQA from different aspects.
Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution
To enlarge RF with contained LUT sizes, we propose a novel Reconstructed Convolution(RC) module, which decouples channel-wise and spatial calculation.
Quality-aware Pre-trained Models for Blind Image Quality Assessment
Blind image quality assessment (BIQA) aims to automatically evaluate the perceived quality of a single image, whose performance has been improved by deep learning-based methods in recent years.
SoftCollage: A Differentiable Probabilistic Tree Generator for Image Collage
While several recent works exploit tree-based algorithm to preserve image content better, all of them resort to hand-crafted adjustment rules to optimize the collage tree structure, leading to the failure of fully exploring the structure space of collage tree.
Aesthetic Photo Collage with Deep Reinforcement Learning
To overcome the lack of training data, we pretrain our deep aesthetic network on a large scale image aesthetic dataset (CPC) for general aesthetic feature extraction and propose an attention fusion module for structural collage feature representation.
Progressive Spatial Recurrent Neural Network for Intra Prediction
With preceding pixels as the context, traditional intra prediction schemes generate linear predictions based on several predefined directions (i. e. modes) for blocks to be encoded.
Joint Enhancement and Denoising Method via Sequential Decomposition
Many low-light enhancement methods ignore intensive noise in original images.
MARLow: A Joint Multiplanar Autoregressive and Low-Rank Approach for Image Completion
In this paper, we propose a novel multiplanar autoregressive (AR) model to exploit the correlation in cross-dimensional planes of a similar patch group collected in an image, which has long been neglected by previous AR models.
