https://github.com/darwen9/ckmimagenet
공식 코드Deep Learning-Based CKM Construction with Image Super-Resolution
Papers with Code 아카이브
Image Super-Resolution
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Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/dasongli1/learning_degradation
공식 코드https://github.com/dawnhh/dlsr-pytorch
공식 코드Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution
https://github.com/dengzeshuai/srtta
공식 코드Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction
https://github.com/diegovalsesia/deepsum
공식 코드DeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal images
https://github.com/diegovalsesia/piunet
공식 코드Permutation invariance and uncertainty in multitemporal image super-resolution
https://github.com/diff7/QuanToaster
공식 코드https://github.com/dingsheng-ong/ipr-gan
공식 코드Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack
https://github.com/dslisleedh/ESC
공식 코드Emulating Self-attention with Convolution for Efficient Image Super-Resolution
https://github.com/dslisleedh/IGConv
공식 코드Implicit Grid Convolution for Multi-Scale Image Super-Resolution
https://github.com/dslisleedh/PLKSR
공식 코드https://github.com/duanlab123/curvpnp
공식 코드CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature Denoiser
https://github.com/dvlab-research/MASA-SR
공식 코드MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution
https://github.com/dvlab-research/Simple-SR
공식 코드https://github.com/ec-jrc/humaint_annotator
공식 코드Attribute Annotation and Bias Evaluation in Visual Datasets for Autonomous Driving
https://github.com/edongdongchen/DDN
공식 코드https://github.com/eduardzamfir/ntire23-rtsr
공식 코드Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey
https://github.com/eduardzamfir/seemoredetails
공식 코드See More Details: Efficient Image Super-Resolution by Experts Mining
https://github.com/eezkni/ddr
공식 코드DDR: Exploiting Deep Degradation Response as Flexible Image Descriptor
https://github.com/eezkni/ssiu
공식 코드Structural Similarity-Inspired Unfolding for Lightweight Image Super-Resolution
https://github.com/egkang-luis/burstm
공식 코드BurstM: Deep Burst Multi-scale SR using Fourier Space with Optical Flow
https://github.com/enter-i-username/eigensr
공식 코드EigenSR: Eigenimage-Bridged Pre-Trained RGB Learners for Single Hyperspectral Image Super-Resolution
https://github.com/esteban-rs/extracter
공식 코드https://github.com/ethz-asl/tulip
공식 코드https://github.com/event-ahu/vfm-det
공식 코드VFM-Det: Towards High-Performance Vehicle Detection via Large Foundation Models
https://github.com/explainableml/bayescap
공식 코드BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks
https://github.com/falsr/FALSR
공식 코드Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search
https://github.com/fanamber831/sgglc-net
공식 코드Semantic-Guided Global-Local Collaborative Networks for Lightweight Image Super-Resolution
https://github.com/fanghua-yu/osrt
공식 코드OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer
https://github.com/fenglinglwb/edt
공식 코드On Efficient Transformer-Based Image Pre-training for Low-Level Vision
https://github.com/francis0625/omni-sr
공식 코드Omni Aggregation Networks for Lightweight Image Super-Resolution
https://github.com/fried-rice-lab/emt
공식 코드Efficient Mixed Transformer for Single Image Super-Resolution
https://github.com/fried-rice-lab/friedricelab
공식 코드Image Super-Resolution using Efficient Striped Window Transformer
https://github.com/fudanvi/fudanocr
공식 코드Text Gestalt: Stroke-Aware Scene Text Image Super-Resolution
https://github.com/fyan111/rlfn
공식 코드Residual Local Feature Network for Efficient Super-Resolution
https://github.com/fzuzyb/ASteISR
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.