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Image Rescaling
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 48
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.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Plug-and-Play Tri-Branch Invertible Block for Image Rescaling
Block-Based Multi-Scale Image Rescaling
Thermal Chameleon: Task-Adaptive Tone-mapping for Radiometric Thermal-Infrared images
Timestep-Aware Diffusion Model for Extreme Image Rescaling
Boundary-aware Decoupled Flow Networks for Realistic Extreme Rescaling
Invertible Residual Rescaling Models
Real-time 6K Image Rescaling with Rate-distortion Optimization
Raising The Limit Of Image Rescaling Using Auxiliary Encoding
Self-Asymmetric Invertible Network for Compression-Aware Image Rescaling
Downscaled Representation Matters: Improving Image Rescaling with Collaborative Downscaled Images
Invertible Rescaling Network and Its Extensions
Effective Invertible Arbitrary Image Rescaling
Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural Network
Towards Bidirectional Arbitrary Image Rescaling: Joint Optimization and Cycle Idempotence
Approaching the Limit of Image Rescaling via Flow Guidance
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
An Image Forensic Technique Based on JPEG Ghosts
Invertible Image Rescaling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.