https://github.com/jingjin25/LFhybridSR-Fusion
공식 코드Light Field Super-resolution via Attention-Guided Fusion of Hybrid Lenses
Papers with Code 아카이브
Super-Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/jingxiaoliu/TelecomTM
공식 코드https://github.com/jingyuanchan/CVPR_AICity_2021_Anomaly_Detection
공식 코드Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing
https://github.com/jingyunliang/hcflow
공식 코드Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling
https://github.com/jingyunliang/manet
공식 코드Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution
https://github.com/jingyunliang/rvrt
공식 코드Recurrent Video Restoration Transformer with Guided Deformable Attention
https://github.com/jingyunliang/swinir
공식 코드https://github.com/jingyunliang/vrt
공식 코드https://github.com/jinnh/pde-net
공식 코드Deep Posterior Distribution-based Embedding for Hyperspectral Image Super-resolution
https://github.com/jinnh/resss-convset
공식 코드Deep Diversity-Enhanced Feature Representation of Hyperspectral Images
https://github.com/jinsuyoo/SSA-VSR
공식 코드https://github.com/jinsuyoo/act
공식 코드Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution
https://github.com/jinxinzhou/dream
공식 코드DREAM: Diffusion Rectification and Estimation-Adaptive Models
https://github.com/jiny2001/dcscn-super-resolution
공식 코드Fast and Accurate Image Super Resolution by Deep CNN with Skip Connection and Network in Network
https://github.com/jinyxp/weather4cast-2022
공식 코드RainUNet for Super-Resolution Rain Movie Prediction under Spatio-temporal Shifts
https://github.com/jiy173/MANA
공식 코드Memory-Augmented Non-Local Attention for Video Super-Resolution
https://github.com/jjunak-yun/FLowHigh_code
공식 코드FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow Matching
https://github.com/jleinonen/downscaling-rnn-gan
공식 코드https://github.com/jm-xiong/rshazediff
공식 코드RSHazeDiff: A Unified Fourier-aware Diffusion Model for Remote Sensing Image Dehazing
https://github.com/jmzhang79/dual-arbnet
공식 코드Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRI
https://github.com/jnuchenyihong/nafrssr
공식 코드NAFRSSR: a Lightweight Recursive Network for Efficient Stereo Image Super-Resolution
https://github.com/jocelyney/gdnet
공식 코드Guidance Disentanglement Network for Optics-Guided Thermal UAV Image Super-Resolution
https://github.com/joeduman/Thresholded_event-based-crossing-dataset
공식 코드https://github.com/joeshenouda/relu-inrs
공식 코드ReLUs Are Sufficient for Learning Implicit Neural Representations
https://github.com/johnromanelis/spvd
공식 코드Efficient and Scalable Point Cloud Generation with Sparse Point-Voxel Diffusion Models
https://github.com/jonathanshani/denoiser_projection
공식 코드Denoiser-based projections for 2-D super-resolution multi-reference alignment
https://github.com/josiahwsmith10/Radar-Musical-Instrument
공식 코드An FCNN-Based Super-Resolution mmWave Radar Framework for Contactless Musical Instrument Interface
https://github.com/josiahwsmith10/josiahwsmith10
공식 코드Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems
https://github.com/josiahwsmith10/spectral-super-resolution-swin
공식 코드Frequency Estimation Using Complex-Valued Shifted Window Transformer
https://github.com/josiahwsmith10/thz-and-sub-thz-imaging-toolbox
공식 코드A Vision Transformer Approach for Efficient Near-Field Irregular SAR Super-Resolution
https://github.com/jqmcginnis/multi_contrast_inr
공식 코드Single-subject Multi-contrast MRI Super-resolution via Implicit Neural Representations
https://github.com/jscanvic/scale-equivariant-imaging
공식 코드Scale-Equivariant Imaging: Self-Supervised Learning for Image Super-Resolution and Deblurring
https://github.com/jspan/PHYSICS_SR
공식 코드https://github.com/jun0kim/dkn
공식 코드https://github.com/junfu1995/sgh
공식 코드Scale Guided Hypernetwork for Blind Super-Resolution Image Quality Assessment
https://github.com/junghunoh/sls_cvpr2022
공식 코드Attentive Fine-Grained Structured Sparsity for Image Restoration
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.