Journals starting with ntir

NTIRE16 * *New Trends in Image Restoration and Enhancement
* Blind Image Deblurring Using Elastic-Net Based Rank Prior
* CNN-GRNN for Image Sharpness Assessment
* Debluring Low-Resolution Images
* Dual Adaptive Regularization Method to Remove Mixed Gaussian-Poisson Noise, A
* Generic 3D Convolutional Fusion for Image Restoration
* Local Feature-Based Photo Album Compression by Eliminating Redundancy of Human Partition
* Low-Rank Tensor Recovery and Alignment Based on Lp Minimization
* Model and Dictionary Guided Face Inpainting in the Wild
* Patch Group Based Bayesian Learning for Blind Image Denoising
* Robust Noisy Image Super-Resolution Using l1-norm Regularization and Non-local Constraint
* Single Image Dehazing Using Fixed Points and Nearest-Neighbor Regularization
* Single Image Super-Resolution Reconstruction Based on Edge-Preserving with External and Internal Gradient Prior Knowledge
* Video Super Resolution Using Non-Local Means with Adaptive Decaying Factor and Searching Window
* Visual Smoke Detection
15 for NTIRE16

NTIRE17 * *New Trends in Image Restoration and Enhancement
* Balanced Two-Stage Residual Networks for Image Super-Resolution
* Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification
* Deep Convolutional Neural Network with Selection Units for Super-Resolution, A
* Deep Wavelet Prediction for Image Super-Resolution
* Depth-Stretch: Enhancing Depth Perception Without Depth
* Enhanced Deep Residual Networks for Single Image Super-Resolution
* Exploiting Reflectional and Rotational Invariance in Single Image Superresolution
* Fast and Accurate Image Super-Resolution Using a Combined Loss
* Fast External Denoising Using Pre-Learned Transformations
* FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos
* FormResNet: Formatted Residual Learning for Image Restoration
* Image Denoising via CNNs: An Adversarial Approach
* Image Super Resolution Based on Fusing Multiple Convolution Neural Networks
* Locally Adaptive Color Correction for Underwater Image Dehazing and Matching
* Multi-Resolution Data Fusion for Super-Resolution Electron Microscopy
* NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study
* NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results
* PaletteNet: Image Recolorization with Given Color Palette
* SRHRF+: Self-Example Enhanced Single Image Super-Resolution Using Hierarchical Random Forests
20 for NTIRE17

NTIRE20 * *New Trends in Image Restoration and Enhancement
* Adaptive Weighted Attention Network with Camera Spectral Sensitivity Prior for Spectral Reconstruction from RGB Images
* C3Net: Demoiréing Network Attentive in Channel, Color and Concatenation
* Color-wise Attention Network for Low-light Image Enhancement
* DA-cGAN: A Framework for Indoor Radio Design Using a Dimension-Aware Conditional Generative Adversarial Network
* Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution
* Deep Wavelet Network with Domain Adaptation for Single Image Demoireing
* Densely Self-guided Wavelet Network for Image Denoising
* Deploying Image Deblurring across Mobile Devices: A Perspective of Quality and Latency
* Dual-domain Deep Convolutional Neural Networks for Image Demoireing
* Ensemble Dehazing Networks for Non-homogeneous Haze
* FabSoften: Face Beautification via Dynamic Skin Smoothing, Guided Feathering, and Texture Restoration
* Fast and Flexible Image Blind Denoising via Competition of Experts
* Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing
* FBRNN: Feedback Recurrent Neural Network for Extreme Image Super-Resolution
* GradNet Image Denoising
* Guided Frequency Separation Network for Real-World SuperResolution
* Hierarchical Regression Network for Spectral Reconstruction from RGB Images
* High-Resolution Dual-Stage Multi-Level Feature Aggregation for Single Image and Video Deblurring
* Identity Enhanced Residual Image Denoising
* ImagePairs: Realistic Super Resolution Dataset via Beam Splitter Camera Rig
* Investigating Loss Functions for Extreme Super-Resolution
* Joint Learning of Blind Video Denoising and Optical Flow Estimation
* Knowledge Transfer Dehazing Network for NonHomogeneous Dehazing
* L2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion
* LIDIA: Lightweight Learned Image Denoising with Instance Adaptation
* MMDM: Multi-frame and Multi-scale for Image Demoiréing
* Moiré Pattern Removal via Attentive Fractal Network
* MSFSR: A Multi-Stage Face Super-Resolution with Accurate Facial Representation via Enhanced Facial Boundaries
* Multi-Step Reinforcement Learning for Single Image Super-Resolution
* NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and Haze-Free Images
* NonLocal Channel Attention for NonHomogeneous Image Dehazing
* NTIRE 2020 Challenge on Image and Video Deblurring
* NTIRE 2020 Challenge on Image Demoireing: Methods and Results
* NTIRE 2020 Challenge on NonHomogeneous Dehazing
* NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
* NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results
* NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results
* NTIRE 2020 Challenge on Spectral Reconstruction from an RGB Image
* NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results
* Perceptual Extreme Super Resolution Network with Receptive Field Block
* Photosequencing of Motion Blur using Short and Long Exposures
* Physically Plausible Spectral Reconstruction from RGB Images
* Real Image Denoising Based on Multi-Scale Residual Dense Block and Cascaded U-Net with Block-Connection
* Real-World Super-Resolution using Generative Adversarial Networks
* Real-World Super-Resolution via Kernel Estimation and Noise Injection
* Rendering Natural Camera Bokeh Effect with Deep Learning
* Replacing Mobile Camera ISP with a Single Deep Learning Model
* Residual Channel Attention Generative Adversarial Network for Image Super-Resolution and Noise Reduction
* Residual Pixel Attention Network for Spectral Reconstruction from RGB Images
* Review of an Old Dilemma: Demosaicking First, or Denoising First?, A
* RGB to Spectral Reconstruction via Learned Basis Functions and Weights
* Semantic Pixel Distances for Image Editing
* Sensor-realistic Synthetic Data Engine for Multi-frame High Dynamic Range Photography
* SimUSR: A Simple but Strong Baseline for Unsupervised Image Super-resolution
* Sky Optimization: Semantically aware image processing of skies in low-light photography
* Structure Preserving Compressive Sensing MRI Reconstruction using Generative Adversarial Networks
* Superkernel Neural Architecture Search for Image Denoising
* Trident Dehazing Network
* Unsupervised Image Super-Resolution with an Indirect Supervised Path
* Unsupervised Real Image Super-Resolution via Generative Variational AutoEncoder
* Unsupervised Real-World Super Resolution with Cycle Generative Adversarial Network and Domain Discriminator
* Unsupervised Single Image Super-Resolution Network (USISResNet) for Real-World Data Using Generative Adversarial Network
63 for NTIRE20

NTIRE21 * *New Trends in Image Restoration and Enhancement
* Adaptive Spatial-Temporal Fusion of Multi-Objective Networks for Compressed Video Perceptual Enhancement
* ADNet: Attention-guided Deformable Convolutional Network for High Dynamic Range Imaging
* ASNA) An Attention-based Siamese-Difference Neural Network with Surrogate Ranking Loss function for Perceptual Image Quality Assessment
* Attention! Stay Focus!
* Beyond Joint Demosaicking and Denoising: An Image Processing Pipeline for a Pixel-bin Image Sensor
* Boosting the Performance of Video Compression Artifact Reduction with Reference Frame Proposals and Frequency Domain Information
* Cross Modality Knowledge Distillation for Multi-modal Aerial View Object Classification
* Deep Learning-based Distortion Sensitivity Prediction for Full-Reference Image Quality Assessment
* DeepObjStyle: Deep Object-based Photo Style Transfer
* Dual Contrastive Learning for Unsupervised Image-to-Image Translation
* DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing
* EBSR: Feature Enhanced Burst Super-Resolution with Deformable Alignment
* Edge Guided Progressively Generative Image Outpainting
* EDPN: Enhanced Deep Pyramid Network for Blurry Image Restoration
* Efficient CNN Architecture for Multi-modal Aerial View Object Classification
* Efficient Space-time Video Super Resolution using Low-Resolution Flow and Mask Upsampling
* EGB: Image Quality Assessment based on Ensemble of Gradient Boosting
* Generic Image Restoration with Flow Based Priors
* Guidance Network with Staged Learning for Image enhancement
* HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization
* HINet: Half Instance Normalization Network for Image Restoration
* Improved Noise2Noise Denoising with Limited Data
* Instagram Filter Removal on Fashionable Images
* IQMA Network: Image Quality Multi-scale Assessment Network
* KernelNet: A Blind Super-Resolution Kernel Estimation Network
* Learning A Cascaded Non-Local Residual Network for Super-resolving Blurry Images
* Long-Tailed Recognition of SAR Aerial View Objects by Cascading and Paralleling Experts
* LTNet: Light Transfer Network for Depth Guided Image Relighting
* Multi-modal Bifurcated Network for Depth Guided Image Relighting
* Multi-Scale Selective Residual Learning for Non-Homogeneous Dehazing
* Multi-scale Self-calibrated Network for Image Light Source Transfer
* Noise Conditional Flow Model for Learning the Super-Resolution Space
* NTIRE 2021 Challenge for Defocus Deblurring Using Dual-pixel Images: Methods and Results
* NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
* NTIRE 2021 Challenge on High Dynamic Range Imaging: Dataset, Methods and Results
* NTIRE 2021 Challenge on Image Deblurring
* NTIRE 2021 Challenge on Perceptual Image Quality Assessment
* NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Dataset and Study
* NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results
* NTIRE 2021 Challenge on Video Super-Resolution
* NTIRE 2021 Depth Guided Image Relighting Challenge
* NTIRE 2021 Learning the Super-Resolution Space Challenge
* NTIRE 2021 Multi-modal Aerial View Object Classification Challenge
* NTIRE 2021 NonHomogeneous Dehazing Challenge Report
* Overparametrization of HyperNetworks at Fixed FLOP-Count Enables Fast Neural Image Enhancement
* Perceptual Image Quality Assessment with Transformers
* Physically Inspired Dense Fusion Networks for Relighting
* Pixel-Guided Dual-Branch Attention Network for Joint Image Deblurring and Super-Resolution
* PnG: Micro-structured Prune-and-Grow Networks for Flexible Image Restoration
* Region-Adaptive Deformable Network for Image Quality Assessment
* Restoration of Video Frames from a Single Blurred Image with Motion Understanding
* Robust Image-to-Image Color Transfer Using Optimal Inlier Maximization
* S3Net: A Single Stream Structure for Depth Guided Image Relighting
* Self-Supervised Multi-Task Pretraining Improves Image Aesthetic Assessment
* Shadow Removal with Paired and Unpaired Learning
* Single Image Dehazing Using Bounded Channel Difference Prior
* Single image HDR synthesis using a Densely Connected Dilated ConvNet
* Single-Image HDR Reconstruction with Task-specific Network based on Channel Adaptive RDN
* SRFlow-DA: Super-Resolution Using Normalizing Flow with Deep Convolutional Block
* SRKTDN: Applying Super Resolution Method to Dehazing Task
* Symmetric Parallax Attention for Stereo Image Super-Resolution
* Three Gaps for Quantisation in Learned Image Compression
* Toward Interactive Modulation for Photo-Realistic Image Restoration
* Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble Learning, A
* Two-stage Deep Network for High Dynamic Range Image Reconstruction, A
* Unifying Guided and Unguided Outdoor Image Synthesis
* Variational AutoEncoder for Reference based Image Super-Resolution
* VSpSR: Explorable Super-Resolution via Variational Sparse Representation
* Weighted Multi-Kernel Prediction Network for Burst Image Super-Resolution
* Wide Receptive Field and Channel Attention Network for JPEG Compressed Image Deblurring
71 for NTIRE21

NTIRE22 * *New Trends in Image Restoration and Enhancement
* Adaptive Feature Consolidation Network for Burst Super-Resolution
* Alpha Matte Generation from Single Input for Portrait Matting
* AnoDDPM: Anomaly Detection with Denoising Diffusion Probabilistic Models using Simplex Noise
* Asymmetric Information Distillation Network for Lightweight Super Resolution
* Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network
* Bidirectional Motion Estimation with Cyclic Cost Volume for High Dynamic Range Imaging
* Blind Non-Uniform Motion Deblurring using Atrous Spatial Pyramid Deformable Convolution and Deblurring-Reblurring Consistency
* Blueprint Separable Residual Network for Efficient Image Super-Resolution
* Boundary-aware Image Inpainting with Multiple Auxiliary Cues
* BSRT: Improving Burst Super-Resolution with SWIN Transformer and Flow-Guided Deformable Alignment
* Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds, A
* Comparison of CoModGANs, LaMa and GLIDE for Art Inpainting Completing M.C Escher's Print Gallery
* Complete and temporally consistent video outpainting
* Conformer and Blind Noisy Students for Improved Image Quality Assessment
* Deep Image Interpolation: A Unified Unsupervised Framework for Pansharpening
* Deep-FlexISP: A Three-Stage Framework for Night Photography Rendering
* Do What You Can, With What You Have: Scale-aware and High Quality Monocular Depth Estimation Without Real World Labels
* DRCR Net: Dense Residual Channel Re-calibration Network with Non-local Purification for Spectral Super Resolution
* DRHDR: A Dual branch Residual Network for Multi-Bracket High Dynamic Range Imaging
* DRT: A Lightweight Single Image Deraining Recursive Transformer
* Dual Heterogeneous Complementary Networks for Single Image Deraining
* Dual-Domain Image Synthesis using Segmentation-Guided GAN
* Edge-enhanced Feature Distillation Network for Efficient Super-Resolution
* Efficient Image Super-Resolution with Collapsible Linear Blocks
* Efficient Progressive High Dynamic Range Image Restoration via Attention and Alignment Network
* Exploiting Distortion Information for Multi-degraded Image Restoration
* Exposure Correction Model to Enhance Image Quality
* Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution
* Fast-n-Squeeze: towards real-time spectral reconstruction from RGB images
* FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing Flow
* Gamma-enhanced Spatial Attention Network for Efficient High Dynamic Range Imaging
* GenISP: Neural ISP for Low-Light Machine Cognition
* GLaMa: Joint Spatial and Frequency Loss for General Image Inpainting
* Hybrid Network of CNN and Transformer for Lightweight Image Super-Resolution, A
* Identity Preserving Loss for Learned Image Compression
* Image Multi-Inpainting via Progressive Generative Adversarial Networks
* Image Quality Assessment with Gradient Siamese Network
* IMDeception: Grouped Information Distilling Super-Resolution Network
* LAN: Lightweight Attention-based Network for RAW-to-RGB Smartphone Image Processing
* Lightweight Network for High Dynamic Range Imaging, A
* MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
* Motion Aware Double Attention Network for Dynamic Scene Deblurring
* MST++: Multi-stage Spectral-wise Transformer for Efficient Spectral Reconstruction
* MSTRIQ: No Reference Image Quality Assessment Based on Swin Transformer with Multi-Stage Fusion
* Multi-Bracket High Dynamic Range Imaging with Event Cameras
* Multi-encoder Network for Parameter Reduction of a Kernel-based Interpolation Architecture
* Multiple Degradation and Reconstruction Network for Single Image Denoising via Knowledge Distillation
* NAFSSR: Stereo Image Super-Resolution Using NAFNet
* New Dataset and Transformer for Stereoscopic Video Super-Resolution, A
* Nighttime Image Dehazing Based on Variational Decomposition Model
* NL-FFC: Non-Local Fast Fourier Convolution for Image Super Resolution
* Nonuniformly Dehaze Network for Visible Remote Sensing Images
* NTIRE 2022 Burst Super-Resolution Challenge
* NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
* NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results
* NTIRE 2022 Challenge on Learning the Super-Resolution Space
* NTIRE 2022 Challenge on Night Photography Rendering
* NTIRE 2022 Challenge on Perceptual Image Quality Assessment
* NTIRE 2022 Challenge on Stereo Image Super-Resolution: Methods and Results
* NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
* NTIRE 2022 Image Inpainting Challenge: Report
* NTIRE 2022 Spectral Demosaicing Challenge and Data Set
* NTIRE 2022 Spectral Recovery Challenge and Data Set
* Online Meta Adaptation for Variable-Rate Learned Image Compression
* Patch-wise Contrastive Style Learning for Instagram Filter Removal
* Progressive Training of A Two-Stage Framework for Video Restoration
* Rendering Nighttime Image Via Cascaded Color and Brightness Compensation
* Residual Local Feature Network for Efficient Super-Resolution
* robust non-blind deblurring method using deep denoiser prior, A
* Self-Calibrated Efficient Transformer for Lightweight Super-Resolution
* SwiniPASSR: Swin Transformer based Parallax Attention Network for Stereo Image Super-Resolution
* Towards Real-world Shadow Removal with a Shadow Simulation Method and a Two-stage Framework
* Transformer for Single Image Super-Resolution
* Underwater Light Field Retention: Neural Rendering for Underwater Imaging
* Unpaired Face Restoration via Learnable Cross-Quality Shift
* Unpaired Real-World Super-Resolution with Pseudo Controllable Restoration
* VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution
* Zoom-to-Inpaint: Image Inpainting with High-Frequency Details
79 for NTIRE22

NTIRE23 * *New Trends in Image Restoration and Enhancement
* Adaptive Human-Centric Video Compression for Humans and Machines
* AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions
* Attention Retractable Frequency Fusion Transformer for Image Super Resolution
* Back to the future: a night photography rendering ISP without deep learning
* BeautyREC: Robust, Efficient, and Component-Specific Makeup Transfer
* Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution
* Bicubic++: Slim, Slimmer, Slimmest Designing an Industry-Grade Super-Resolution Network
* Blind Image Inpainting via Omni-dimensional Gated Attention and Wavelet Queries
* BokehOrNot: Transforming Bokeh Effect with Image Transformer and Lens Metadata Embedding
* Breaking Through the Haze: An Advanced Non-Homogeneous Dehazing Method based on Fast Fourier Convolution and ConvNeXt
* Cross-View Hierarchy Network for Stereo Image Super-Resolution
* Data-Centric Solution to NonHomogeneous Dehazing via Vision Transformer, A
* Deep Dehazing Powered by Image Processing Network
* Denoising Diffusion Models for Plug-and-Play Image Restoration
* DIPNet: Efficiency Distillation and Iterative Pruning for Image Super-Resolution
* DistgEPIT: Enhanced Disparity Learning for Light Field Image Super-Resolution
* Efficient Deep Models for Real-Time 4K Image Super-Resolution. NTIRE 2023 Benchmark and Report
* Efficient Multi-Lens Bokeh Effect Rendering and Transformation
* Expanding Synthetic Real-World Degradations for Blind Video Super Resolution
* FlexiCurve: Flexible Piecewise Curves Estimation for Photo Retouching
* FRR-Net: A Real-Time Blind Face Restoration and Relighting Network
* High-Perceptual Quality JPEG Decoding via Posterior Sampling
* High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation
* Hybrid Transformer and CNN Attention Network for Stereo Image Super-resolution
* Large Kernel Distillation Network for Efficient Single Image Super-Resolution
* Learning Epipolar-Spatial Relationship for Light Field Image Super-Resolution
* Lens-to-Lens Bokeh Effect Transformation. NTIRE 2023 Challenge Report
* Lightweight Real-Time Image Super-Resolution Network for 4K Images
* LSDIR: A Large Scale Dataset for Image Restoration
* Mixer-based Local Residual Network for Lightweight Image Super-resolution
* Multi-level Dispersion Residual Network for Efficient Image Super-Resolution
* NAFBET: Bokeh Effect Transformation with Parameter Analysis Block based on NAFNet
* NTIRE 2023 Challenge on 360° Omnidirectional Image and Video Super-Resolution: Datasets, Methods and Results
* NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results
* NTIRE 2023 Challenge on HR Depth from Images of Specular and Transparent Surfaces
* NTIRE 2023 Challenge on Image Denoising: Methods and Results
* NTIRE 2023 Challenge on Image Super-Resolution (×4): Methods and Results
* NTIRE 2023 Challenge on Light Field Image Super-Resolution: Dataset, Methods and Results
* NTIRE 2023 Challenge on Night Photography Rendering
* NTIRE 2023 Challenge on Stereo Image Super-Resolution: Methods and Results
* NTIRE 2023 HR NonHomogeneous Dehazing Challenge Report
* NTIRE 2023 Image Shadow Removal Challenge Report
* NTIRE 2023 Quality Assessment of Video Enhancement Challenge
* NTIRE 2023 Video Colorization Challenge
* OPDN: Omnidirectional Position-aware Deformable Network for Omnidirectional Image Super-Resolution
* ProgDTD: Progressive Learned Image Compression with Double-Tail-Drop Training
* Pyramid Ensemble Structure for High Resolution Image Shadow Removal
* Quality assessment of enhanced videos guided by aesthetics and technical quality attributes
* Quantum Annealing for Single Image Super-Resolution
* RB-Dust - A Reference-based Dataset for Vision-based Dust Removal
* Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
* Reparameterized Residual Feature Network For Lightweight Image Super-Resolution
* Rip Current Segmentation: A Novel Benchmark and YOLOv8 Baseline Results
* RTTLC: Video Colorization with Restored Transformer and Test-time Local Converter
* Saliency-aware Stereoscopic Video Retargeting
* SB-VQA: A Stack-Based Video Quality Assessment Framework for Video Enhancement
* SC-NAFSSR: Perceptual-Oriented Stereo Image Super-Resolution Using Stereo Consistency Guided NAFSSR
* SCANet: Self-Paced Semi-Curricular Attention Network for Non-Homogeneous Image Dehazing
* SCONE-GAN: Semantic Contrastive learning-based Generative Adversarial Network for an end-to-end image translation
* Selective Bokeh Effect Transformation
* Semantic Guidance Learning for High-Resolution Non-homogeneous Dehazing
* Simple Transformer-style Network for Lightweight Image Super-resolution, A
* Single Residual Network with ESA Modules and Distillation, A
* Spatial-Angular Multi-Scale Mechanism for Light Field Spatial Super-Resolution
* SS-TTA: Test-Time Adaption for Self-Supervised Denoising Methods
* Stereo Cross Global Learnable Attention Module for Stereo Image Super-Resolution
* Streamlined Global and Local Features Combinator (SGLC) for High Resolution Image Dehazing
* SwinFSR: Stereo Image Super-Resolution using SwinIR and Frequency Domain Knowledge
* Temporal Consistent Automatic Video Colorization via Semantic Correspondence
* Towards Real-Time 4K Image Super-Resolution
* TransER: Hybrid Model and Ensemble-based Sequential Learning for Non-homogenous Dehazing
* TSRFormer: Transformer Based Two-stage Refinement for Single Image Shadow Removal
* Unlimited-Size Diffusion Restoration
* VDPVE: VQA Dataset for Perceptual Video Enhancement
* Video Quality Assessment Based on Swin Transformer with Spatio-Temporal Feature Fusion and Data Augmentation
* WSRD: A Novel Benchmark for High Resolution Image Shadow Removal
* Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment
78 for NTIRE23

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