SSIM
302 papers with code • 1 benchmarks • 4 datasets
Libraries
Use these libraries to find SSIM models and implementations
O-HAZE
I-HAZE
VIDIT
DRealSR
Latest papers with no code
On Generating Cancelable Biometric Template using Reverse of Boolean XOR
Cancelable Biometric is repetitive distortion embedded in original Biometric image for keeping it secure from unauthorized access.
CrossScore: Towards Multi-View Image Evaluation and Scoring
We introduce a novel cross-reference image quality assessment method that effectively fills the gap in the image assessment landscape, complementing the array of established evaluation schemes -- ranging from full-reference metrics like SSIM, no-reference metrics such as NIQE, to general-reference metrics including FID, and Multi-modal-reference metrics, e. g., CLIPScore.
SEGSRNet for Stereo-Endoscopic Image Super-Resolution and Surgical Instrument Segmentation
SEGSRNet addresses the challenge of precisely identifying surgical instruments in low-resolution stereo endoscopic images, a common issue in medical imaging and robotic surgery.
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention Blocks
We propose a new multi-picture architecture for video deinterlacing or demosaicing by aligning multiple supporting pictures with missing data to a reference picture to be reconstructed, benefiting from both local and global spatio-temporal correlations in the feature space using modified deformable convolution blocks and a novel residual efficient top-$k$ self-attention (kSA) block, respectively.
Assessing The Impact of CNN Auto Encoder-Based Image Denoising on Image Classification Tasks
The goal is to enhance the accuracy and robustness of defect detection by integrating noise detection and denoising into the classification pipeline.
PNeRV: Enhancing Spatial Consistency via Pyramidal Neural Representation for Videos
To address this issue, we introduce the Pyramidal Neural Representation for Videos (PNeRV), which is built on a multi-scale information connection and comprises a lightweight rescaling operator, Kronecker Fully-connected layer (KFc), and a Benign Selective Memory (BSM) mechanism.
MonoPatchNeRF: Improving Neural Radiance Fields with Patch-based Monocular Guidance
Our experiments show 4x the performance of RegNeRF and 8x that of FreeNeRF on average F1@2cm for ETH3D MVS benchmark, suggesting a fruitful research direction to improve the geometric accuracy of NeRF-based models, and sheds light on a potential future approach to enable NeRF-based optimization to eventually outperform traditional MVS.
Depth Estimation using Weighted-loss and Transfer Learning
The optimized loss function is a combination of weighted losses to which enhance robustness and generalization: Mean Absolute Error (MAE), Edge Loss and Structural Similarity Index (SSIM).
Self-supervised Monocular Depth Estimation on Water Scenes via Specular Reflection Prior
Monocular depth estimation from a single image is an ill-posed problem for computer vision due to insufficient reliable cues as the prior knowledge.
GauU-Scene V2: Assessing the Reliability of Image-Based Metrics with Expansive Lidar Image Dataset Using 3DGS and NeRF
The experimental results on our multimodal dataset highlight the unreliability of current image-based metrics and reveal significant drawbacks in geometric reconstruction using the current Gaussian Splatting-based method, further illustrating the necessity of our dataset for assessing geometry reconstruction tasks.
