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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/kritiksoman/GIMP-ML

공식 코드

GIMP-ML: Python Plugins for using Computer Vision Models in GIMP

https://github.com/krulllab/DVLAE

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Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise

https://github.com/krulllab/cosdd

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Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise

https://github.com/krulllab/gap

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Image Denoising and the Generative Accumulation of Photons

https://github.com/kshitij79/CS-7476-Improvements-in-Diffusion-Model

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Enhancing Conditional Image Generation with Explainable Latent Space Manipulation

https://github.com/kuai-lab/soundini-official

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Soundini: Sound-Guided Diffusion for Natural Video Editing

https://github.com/kugamaxx/cuke-emlb

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E-MLB: Multilevel Benchmark for Event-Based Camera Denoising

https://github.com/kugwzk/at_diff

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Improved Diffusion-based Generative Model with Better Adversarial Robustness

https://github.com/kuis-ai-tekalp-research-group/video-deinterlacing

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A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention Blocks

https://github.com/kuleshov-group/bd3lms

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Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models

https://github.com/kurtlabuw/re-diffinet

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Re-DiffiNet: Modeling discrepancies in tumor segmentation using diffusion models

https://github.com/kvablack/ddpo-pytorch

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Training Diffusion Models with Reinforcement Learning

https://github.com/kvfrans/shortcut-models

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One Step Diffusion via Shortcut Models

https://github.com/kwang2049/pytorch-bertflow

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TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

https://github.com/kwang2049/useb

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TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

https://github.com/kxh001/itdiffusion

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Information-Theoretic Diffusion

https://github.com/kylelo/roofdiffusion

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RoofDiffusion: Constructing Roofs from Severely Corrupted Point Data via Diffusion

https://github.com/l-yezhu/boundarydiffusion

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Boundary Guided Learning-Free Semantic Control with Diffusion Models

https://github.com/l-yezhu/cdcd

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Discrete Contrastive Diffusion for Cross-Modal Music and Image Generation

https://github.com/lab-emi/cleanumamba

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CleanUMamba: A Compact Mamba Network for Speech Denoising using Channel Pruning

https://github.com/labforcomputationalvision/local-probability-models-of-images

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Learning multi-scale local conditional probability models of images

https://github.com/labforcomputationalvision/memorization_generalization_in_diffusion_models

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Generalization in diffusion models arises from geometry-adaptive harmonic representations

https://github.com/laizhr/irm-tv

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Invariant Risk Minimization Is A Total Variation Model

https://github.com/lakonik/gmflow

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Gaussian Mixture Flow Matching Models

https://github.com/lalunex/msdccl

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Multi-Level Sequence Denoising with Cross-Signal Contrastive Learning for Sequential Recommendation

https://github.com/lamomal/multisv

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MultiSV: Dataset for Far-Field Multi-Channel Speaker Verification

https://github.com/lancezpf/seeds

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SeeDS: Semantic Separable Diffusion Synthesizer for Zero-shot Food Detection

https://github.com/lanzhang128/retrieval_augmented_autoformalization

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Consistent Autoformalization for Constructing Mathematical Libraries

https://github.com/laowangbobo/residual_mlp_cnn_mixer

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Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence

https://github.com/larsdoorenbos/ccdm-stochastic-segmentation

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Stochastic Segmentation with Conditional Categorical Diffusion Models

https://github.com/layer6ai-labs/denoising_dgms

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Denoising Deep Generative Models

https://github.com/lcav/lenslesspicam

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LenslessPiCam: A Hardware and Software Platform for Lensless Computational Imaging with a Raspberry Pi

https://github.com/lcbkmm/tc-kanrecon

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TC-KANRecon: High-Quality and Accelerated MRI Reconstruction via Adaptive KAN Mechanisms and Intelligent Feature Scaling

https://github.com/leaplabthu/attention-mediators

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Efficient Diffusion Transformer with Step-wise Dynamic Attention Mediators

https://github.com/led-666/ttrd3

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TTRD3: Texture Transfer Residual Denoising Dual Diffusion Model for Remote Sensing Image Super-Resolution

https://github.com/lefteyex/u-decn

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U-DECN: End-to-End Underwater Object Detection ConvNet with Improved DeNoising Training

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.