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3D Architecture

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/zju-pi/awesome-conditional-diffusion-models

공식 코드

Conditional Image Synthesis with Diffusion Models: A Survey

https://github.com/zju-pi/diff-sampler

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A Geometric Perspective on Diffusion Models

https://github.com/zkccz/stbn

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Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for Self-Supervised Video Denoising

https://github.com/zmtomorrow/mmdgs_neurips

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Moment Matching Denoising Gibbs Sampling

https://github.com/zoukaifeng/4dfm

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4D Facial Expression Diffusion Model

https://github.com/zpengmei/geom2vec

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Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics

https://github.com/zpf0117b/CLMB

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CLMB: deep contrastive learning for robust metagenomic binning

https://github.com/zphang/usc_dae

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Unsupervised Sentence Compression using Denoising Auto-Encoders

https://github.com/zplusdragon/cion_reidzoo

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Cross-video Identity Correlating for Person Re-identification Pre-training

https://github.com/zrealli/TIGIC

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Tuning-Free Image Customization with Image and Text Guidance

https://github.com/zrgcityu/graph-involved-frame

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Data-Adaptive Graph Framelets with Generalized Vanishing Moments for Graph Signal Processing

https://github.com/zsc15/HPPP

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HPPP: Halpern-type Preconditioned Proximal Point Algorithms and Applications to Image Restoration

https://github.com/zsyOAOA/DANet

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Dual Adversarial Network: Toward Real-world Noise Removal and Noise Generation

https://github.com/zsyOAOA/VDNet

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Variational Denoising Network: Toward Blind Noise Modeling and Removal

https://github.com/zsyOAOA/VIRNet

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Deep Variational Network Toward Blind Image Restoration

https://github.com/zubaerimran/SSWL-IDN

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Window-Level is a Strong Denoising Surrogate

https://github.com/zwang78/moediff-sr

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MoEDiff-SR: Mixture of Experts-Guided Diffusion Model for Region-Adaptive MRI Super-Resolution

https://github.com/zwkatgithub/HGL

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Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model

https://github.com/zwxu064/MPLayers

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Fast and Differentiable Message Passing on Pairwise Markov Random Fields

https://github.com/zx-pan/mdm

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Masked Diffusion as Self-supervised Representation Learner

https://github.com/zy2219105/ct-mamba

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CT-Mamba: A Hybrid Convolutional State Space Model for Low-Dose CT Denoising

https://github.com/zylipku/IterativeImaging

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Spend Wisely: Maximizing Post-Training Gains in Iterative Synthetic Data Boostrapping

https://github.com/zymvszym/ExactDreamer

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ExactDreamer: High-Fidelity Text-to-3D Content Creation via Exact Score Matching

https://github.com/zyxelsa/InST

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Inversion-Based Style Transfer with Diffusion Models

https://github.com/zzmeei/adaptivegcl

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Adaptive Graph Contrastive Learning for Recommendation

https://gitlab.cg.tuwien.ac.at/srasoulzadeh/archcomplete.git

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ArchComplete: Autoregressive 3D Architectural Design Generation with Hierarchical Diffusion-Based Upsampling

https://gitlab.com/UM-CDS/low-dose-ct-denoising

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Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study

https://gitlab.com/a_floquet/automatic-tuning-of-denoising-algorithms-parameters-without-ground-truth

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Automatic Tuning of Denoising Algorithms Parameters Without Ground Truth

https://gitlab.com/cian.unibas.ch/diffusion-anomaly

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Diffusion Models for Medical Anomaly Detection

https://gitlab.com/cian.unibas.ch/sneakynet

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Improved distinct bone segmentation in upper-body CT through multi-resolution networks

https://gitlab.com/elie-chedemail/dp-graph-denoising

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Large Graph Signal Denoising with Application to Differential Privacy

https://gitlab.com/trougnouf/rawnind_jddc

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Learning Joint Denoising, Demosaicing, and Compression from the Raw Natural Image Noise Dataset

https://gitlab.telecom-paris.fr/RING/MERLIN

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As if by magic: self-supervised training of deep despeckling networks with MERLIN

https://gitlab.telecom-paris.fr/RING/SAR-CNN

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SAR Image Despeckling by Deep Neural Networks: from a pre-trained model to an end-to-end training strategy

https://gitlab.telecom-paris.fr/RING/SAR2SAR

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SAR2SAR: a semi-supervised despeckling algorithm for SAR images

https://huggingface.co/spaces/PaddlePaddle/ERNIE-ViLG

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ERNIE-ViLG 2.0: Improving Text-to-Image Diffusion Model with Knowledge-Enhanced Mixture-of-Denoising-Experts

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