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Image Rescaling

Image rescaling is a bidirectional operation, which first downscales high-resolution images to fit various display screens or to be storage- and bandwidth-friendly, and afterward upscales the corresponding low-resolution images to recover the original resolution or the details in the zoom-in images.

Papers

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Showing 1–22 of 22 papers

TitleStatusHype
Invertible Rescaling Network and Its ExtensionsCode2
Plug-and-Play Tri-Branch Invertible Block for Image RescalingCode1
Invertible Image RescalingCode1
Self-Asymmetric Invertible Network for Compression-Aware Image RescalingCode1
Thermal Chameleon: Task-Adaptive Tone-mapping for Radiometric Thermal-Infrared imagesCode1
Faithful Extreme Rescaling via Generative Prior Reciprocated Invertible RepresentationsCode1
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image RescalingCode1
Real-time 6K Image Rescaling with Rate-distortion OptimizationCode1
Boundary-aware Decoupled Flow Networks for Realistic Extreme RescalingCode0
DINN360: Deformable Invertible Neural Network for Latitude-Aware 360deg Image RescalingCode0
Invertible Residual Rescaling ModelsCode0
Geolocating Earth Imagery from ISS: Integrating Machine Learning with Astronaut Photography for Enhanced Geographic MappingCode0
Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural NetworkCode0
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence—0
Approaching the Limit of Image Rescaling via Flow Guidance—0
Block-Based Multi-Scale Image Rescaling—0
Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images—0
Effective Invertible Arbitrary Image Rescaling—0
Raising The Limit Of Image Rescaling Using Auxiliary Encoding—0
Timestep-Aware Diffusion Model for Extreme Image Rescaling—0
Towards a Universal Model for Cross-Dataset Crowd Counting—0
An Image Forensic Technique Based on JPEG Ghosts—0
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