SOTAVerified

SSIM

Papers

Showing 101125 of 1336 papers

TitleStatusHype
FUNQUE: Fusion of Unified Quality EvaluatorsCode1
FusionFrames: Efficient Architectural Aspects for Text-to-Video Generation PipelineCode1
BASNet: Boundary-Aware Salient Object DetectionCode1
Gradient-Based Geometry Learning for Fan-Beam CT ReconstructionCode1
Asymmetric Gained Deep Image Compression With Continuous Rate AdaptationCode1
HazeSpace2M: A Dataset for Haze Aware Single Image DehazingCode1
Image Demoireing in RAW and sRGB DomainsCode1
IM-MoCo: Self-supervised MRI Motion Correction using Motion-Guided Implicit Neural RepresentationsCode1
Advancing Learned Video Compression with In-loop Frame PredictionCode1
Improving the Perceptual Quality of 2D Animation InterpolationCode1
BemaGANv2: A Tutorial and Comparative Survey of GAN-based Vocoders for Long-Term Audio GenerationCode1
A Simple and Efficient Reconstruction Backbone for Snapshot Compressive ImagingCode1
iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection NetworksCode1
iSeeBetter: Spatio-temporal video super-resolution using recurrent generative back-projection networksCode1
Joint Learning Content and Degradation Aware Feature for Blind Super-ResolutionCode1
LapisGS: Layered Progressive 3D Gaussian Splatting for Adaptive StreamingCode1
Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical ImagingCode1
Latent Diffusion Model-Enabled Low-Latency Semantic Communication in the Presence of Semantic Ambiguities and Wireless Channel NoisesCode1
A deep network for sinogram and CT image reconstructionCode1
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability ModelCode1
Learning Spatial Attention for Face Super-ResolutionCode1
Learning to Improve Image Compression without Changing the Standard DecoderCode1
Bidirectional Stereo Image Compression with Cross-Dimensional Entropy ModelCode1
LSwinSR: UAV Imagery Super-Resolution based on Linear Swin TransformerCode1
Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical ImagingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RectiNetSSIM0.55Unverified
2RectiNet-v2SSIM0.51Unverified
3DewarpNetSSIM0.49Unverified
4DocUNetSSIM0.41Unverified