https://github.com/acecreamu/deep-hs-prior
공식 코드Deep Hyperspectral Prior: Denoising, Inpainting, Super-Resolution
Papers with Code 아카이브
Super-Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 보존된 평가 기록
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Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.
<span style="color:grey; opacity: 0.6">( Credit: MemNet )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/adalca/papago
공식 코드https://github.com/adamian98/pulse
공식 코드PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models
https://github.com/aeromamba-super-resolution/aeromamba
공식 코드https://github.com/aesrgan/A-ESRGAN
공식 코드A-ESRGAN: Training Real-World Blind Super-Resolution with Attention U-Net Discriminators
https://github.com/agusgun/cisr
공식 코드https://github.com/ahogg/hrtf-upsampling-with-a-generative-adversarial-network-using-a-gnomonic-equiangular-projection
공식 코드HRTF upsampling with a generative adversarial network using a gnomonic equiangular projection
https://github.com/ai-forever/ghost
공식 코드A new face swap method for image and video domains: a technical report
https://github.com/ai-forever/kandinsky-3
공식 코드https://github.com/ai4netzero/infinite_texture_gans
공식 코드Local Padding in Patch-Based GANs for Seamless Infinite-Sized Texture Synthesis
https://github.com/aimerykong/predictive-filter-flow
공식 코드https://github.com/aimiokab/misr-s2
공식 코드Cross-sensor super-resolution of irregularly sampled Sentinel-2 time series
https://github.com/aitical/cfsr
공식 코드Transforming Image Super-Resolution: A ConvFormer-based Efficient Approach
https://github.com/aitical/scnet
공식 코드Fully $1\times1$ Convolutional Network for Lightweight Image Super-Resolution
https://github.com/aitical/sscsr
공식 코드Exploiting Self-Supervised Constraints in Image Super-Resolution
https://github.com/aitical/tcsr
공식 코드Incorporating Transformer Designs into Convolutions for Lightweight Image Super-Resolution
https://github.com/ajiljalal/code-cs-fairness
공식 코드Fairness for Image Generation with Uncertain Sensitive Attributes
https://github.com/akashpalrecha/hyperspectral-reconstruction
공식 코드https://github.com/akgokce/EndoL2H
공식 코드https://github.com/akshaydudhane16/bipnet
공식 코드https://github.com/akshaydudhane16/burstormer
공식 코드Burstormer: Burst Image Restoration and Enhancement Transformer
https://github.com/alanqrwang/hyperrecon
공식 코드Computing Multiple Image Reconstructions with a Single Hypernetwork
https://github.com/alexandrosstergiou/adaPool
공식 코드AdaPool: Exponential Adaptive Pooling for Information-Retaining Downsampling
https://github.com/alexzou14/cvhssr
공식 코드Cross-View Hierarchy Network for Stereo Image Super-Resolution
https://github.com/alexzou14/scet
공식 코드Self-Calibrated Efficient Transformer for Lightweight Super-Resolution
https://github.com/algolzw/bsrt
공식 코드BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment
https://github.com/algolzw/image-restoration-sde
공식 코드Image Restoration with Mean-Reverting Stochastic Differential Equations
https://github.com/algolzw/ncnet
공식 코드Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution
https://github.com/alifbinabdulqayyum/multi-altitude-inn
공식 코드https://github.com/alik033/lit-net
공식 코드Harnessing Multi-resolution and Multi-scale Attention for Underwater Image Restoration
https://github.com/alik033/ml-craist
공식 코드https://github.com/alimd94/fedvsr
공식 코드FedVSR: Towards Model-Agnostic Federated Learning in Video Super-Resolution
https://github.com/alireza-aghelan/ig-cfat
공식 코드https://github.com/allard-shi/affirm
공식 코드https://github.com/allenai/satlas-super-resolution
공식 코드Zooming Out on Zooming In: Advancing Super-Resolution for Remote Sensing
https://github.com/alphacatplus/vmambair
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.