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Found 15 papers, 1 papers with code
Beyond Night Visibility: Adaptive Multi-Scale Fusion of Infrared and Visible Images
Thereby, we obtain an image free of low light and light effects, which improves the performance of nighttime object detection.
Non-Intrusive Electric Load Monitoring Approach Based on Current Feature Visualization for Smart Energy Management
In this paper, we employ the popular computer vision techniques of AI to design a non-invasive load monitoring method for smart electric energy management.
Geometry-based spherical JND modeling for 360$^\circ$ display
Second, we extend our 2D-JND model to SJND by jointly exploiting latitude projection and field of view during 360$^\circ$ display.
Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment
In this paper, we investigate the influence of four spatial PEAs (i. e. blurring, blocking, bleeding, and ringing) and two temporal PEAs (i. e. flickering and floating) on video quality.
LMQFormer: A Laplace-Prior-Guided Mask Query Transformer for Lightweight Snow Removal
Secondly, we design a Mask Query Transformer (MQFormer) to remove snow with the coarse mask, where we use two parallel encoders and a hybrid decoder to learn extensive snow features under lightweight requirements.
Ranked #1 on
Snow Removal
on SRRS
UIF: An Objective Quality Assessment for Underwater Image Enhancement
In addition, we have also established a large-scale UIE database with subjective scores, namely Underwater Image Enhancement Database (UIED), which is utilized as a benchmark to compare all objective metrics.
Utility-Oriented Underwater Image Quality Assessment Based on Transfer Learning
Based on this task, we build an Underwater Image Utility Database (UIUD) and a learning-based Underwater Image Utility Measure (UIUM).
SPQE: Structure-and-Perception-Based Quality Evaluation for Image Super-Resolution
By combining the quality scores and their weights, we propose a unified SPQE metric for SR-IQA.
Deep Quality Assessment of Compressed Videos: A Subjective and Objective Study
In this work, a semi-automatic labeling method is adopted to build a large-scale compressed video quality database, which allows us to label a large number of compressed videos with manageable human workload.
GAN-Based Multi-View Video Coding with Spatio-Temporal EPI Reconstruction
At the decoder side, we combine the SI and adjacent viewpoints to reconstruct intermediate views using the GAN generator.
Efficient VVC Intra Prediction Based on Deep Feature Fusion and Probability Estimation
The ever-growing multimedia traffic has underscored the importance of effective multimedia codecs.
Learning-Based Video Coding with Joint Deep Compression and Enhancement
Second, we reuse the DPEG network in both motion compensation and quality enhancement modules, which are further combined with other necessary modules to formulate our JCEVC framework.
Contrastive Semantic Similarity Learning for Image Captioning Evaluation with Intrinsic Auto-encoder
Motivated by the auto-encoder mechanism and contrastive representation learning advances, we propose a learning-based metric for image captioning, which we call Intrinsic Image Captioning Evaluation($I^2CE$).
Learning-Based Quality Assessment for Image Super-Resolution
Image Super-Resolution (SR) techniques improve visual quality by enhancing the spatial resolution of images.
PEA265: Perceptual Assessment of Video Compression Artifacts
To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs.
