https://bitbucket.org/fengshi421/superresolutiontoolkit
공식 코드A Tensor Factorization Method for 3D Super-Resolution with Application to Dental CT
Papers with Code 아카이브
3D Object Super-Resolution
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 0
- 보존된 평가 기록
- 0
3D object super-resolution is the task of up-sampling 3D objects.
<span style="color:grey; opacity: 0.6">( Image credit: Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://git5.cs.fau.de/folle/sr-cest
공식 코드Towards Super-Resolution CEST MRI for Visualization of Small Structures
https://gitee.com/wen--he/AMRSR
공식 코드Attention-based Multi-Reference Learning for Image Super-Resolution
https://github.com/11710615/pamsr
공식 코드https://github.com/2minkyulee/aesop-auto-encoded-supervision-for-perceptual-image-super-resolution
공식 코드Auto-Encoded Supervision for Perceptual Image Super-Resolution
https://github.com/2minkyulee/eco
공식 코드Noise-free Optimization in Early Training Steps for Image Super-Resolution
https://github.com/2y7c3/super-resolution-neural-operator
공식 코드https://github.com/3587jjh/lsrna
공식 코드Latent Space Super-Resolution for Higher-Resolution Image Generation with Diffusion Models
https://github.com/5k5000/cldetection2023
공식 코드https://github.com/AMD-AIG-AIMA/DoSSR
공식 코드Taming Diffusion Prior for Image Super-Resolution with Domain Shift SDEs
https://github.com/ARM-software/sesr
공식 코드Collapsible Linear Blocks for Super-Efficient Super Resolution
https://github.com/AbdulMoqeet/HRAN
공식 코드Hybrid Residual Attention Network for Single Image Super Resolution
https://github.com/AdaptiveVC/SRVC
공식 코드Efficient Video Compression via Content-Adaptive Super-Resolution
https://github.com/Ahn-Ssu/VCM
공식 코드Volumetric Conditioning Module to Control Pretrained Diffusion Models for 3D Medical Images
https://github.com/Aitical/MCLIR
공식 코드Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration
https://github.com/Aitical/PCL-SISR
공식 코드A Practical Contrastive Learning Framework for Single-Image Super-Resolution
https://github.com/AlanZhang1995/TwoStreamSR
공식 코드Two-Stream Action Recognition-Oriented Video Super-Resolution
https://github.com/Amirhossein-Nayebi/Nordic-Vehicle-Dataset
공식 코드https://github.com/Arnontu/DeepAudioWaveformPrior
공식 코드https://github.com/ArshockAbedan/CS_MSc_Codes
공식 코드Multi-Modality Image Super-Resolution using Generative Adversarial Networks
https://github.com/Ascend-Research/Turtle
공식 코드Learning Truncated Causal History Model for Video Restoration
https://github.com/BBillot/SynthSR
공식 코드https://github.com/Bala93/KD-MRI
공식 코드https://github.com/BarCodeReader/SelfReformer
공식 코드SelfReformer: Self-Refined Network with Transformer for Salient Object Detection
https://github.com/BenjaminJonghyun/EIPNet
공식 코드Edge and Identity Preserving Network for Face Super-Resolution
https://github.com/BookerDeWitt/GFN-IJCV
공식 코드https://github.com/Booooooooooo/CSD
공식 코드Towards Compact Single Image Super-Resolution via Contrastive Self-distillation
https://github.com/Brian-Moser/zido
공식 코드https://github.com/CAMMA-public/ORPose-Depth
공식 코드Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images
https://github.com/CS-GangXu/TMNet
공식 코드Temporal Modulation Network for Controllable Space-Time Video Super-Resolution
https://github.com/CSU-BME/pathology_MSR
공식 코드Multi-scale super-resolution generation of low-resolution scanned pathological images
https://github.com/CapsuleEndoscope/EndoL2H
공식 코드https://github.com/ChaofWang/AWSRN
공식 코드Lightweight Image Super-Resolution with Adaptive Weighted Learning Network
https://github.com/Cheeun/AdaBM
공식 코드AdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution
https://github.com/Cheeun/DAQ-pytorch
공식 코드DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks
https://github.com/Chernobyllight/ReDSR
공식 코드Preserving Full Degradation Details for Blind Image Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.