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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/tyshiwo/MemNet

공식 코드

MemNet: A Persistent Memory Network for Image Restoration

https://github.com/ubc-vision/StableKeypoints

공식 코드

Unsupervised Keypoints from Pretrained Diffusion Models

https://github.com/ubcdingxin/ccdm

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CCDM: Continuous Conditional Diffusion Models for Image Generation

https://github.com/ucla-starai/tiramisu

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Image Inpainting via Tractable Steering of Diffusion Models

https://github.com/uclaopt/Provable_Plug_and_Play

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Plug-and-Play Methods Provably Converge with Properly Trained Denoisers

https://github.com/ucsb-nlp-chang/copaint

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Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models

https://github.com/ucsb-nlp-chang/diffusion-spacetime-attn

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Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis

https://github.com/ucsb-nlp-chang/diffusiondisentanglement

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Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models

https://github.com/ucsb-nlp-chang/selfdenoise

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Certified Robustness for Large Language Models with Self-Denoising

https://github.com/ucsc-vlaa/microdiffusion

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MicroDiffusion: Implicit Representation-Guided Diffusion for 3D Reconstruction from Limited 2D Microscopy Projections

https://github.com/ucsfncl/dmri-swin

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Generative AI for Rapid Diffusion MRI with Improved Image Quality, Reliability and Generalizability

https://github.com/udibr/LRE

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A Semisupervised Approach for Language Identification based on Ladder Networks

https://github.com/udonda/structure_guided_diffusion_model

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A Structure-Guided Diffusion Model for Large-Hole Image Completion

https://github.com/udrs/gcd

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GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPM

https://github.com/uds-lsv/3st

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Exploiting Social Media Content for Self-Supervised Style Transfer

https://github.com/uhh-lt/mangosteen

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Improving Hypernymy Extraction with Distributional Semantic Classes

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

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

https://github.com/umarkhalidAI/LatentEditor

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LatentEditor: Text Driven Local Editing of 3D Scenes

https://github.com/uni-medical/sam-med3d

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SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

https://github.com/unicomai/shortdf

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Optimizing for the Shortest Path in Denoising Diffusion Model

https://github.com/unimodal4reasoning/adaptivediffusion

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Training-Free Adaptive Diffusion with Bounded Difference Approximation Strategy

https://github.com/univ-esuty/noisecollage

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NoiseCollage: A Layout-Aware Text-to-Image Diffusion Model Based on Noise Cropping and Merging

https://github.com/unknownue/pdflow

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PD-Flow: A Point Cloud Denoising Framework with Normalizing Flows

https://github.com/utat-ss/FINCH-destriping

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Beyond the Visible: Jointly Attending to Spectral and Spatial Dimensions with HSI-Diffusion for the FINCH Spacecraft

https://github.com/utcsilab/gsure-diffusion-mri

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Robust multi-coil MRI reconstruction via self-supervised denoising

https://github.com/uw-madison-lee-lab/sft-pg

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Optimizing DDPM Sampling with Shortcut Fine-Tuning

https://github.com/va1shn9v/promptir

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PromptIR: Prompting for All-in-One Blind Image Restoration

https://github.com/vahanarsenian/diffusionwasserstein

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Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal Bounds

https://github.com/vainf/remix-dit

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Remix-DiT: Mixing Diffusion Transformers for Multi-Expert Denoising

https://github.com/vchleung/LearningBasedFRI

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Learning-Based Reconstruction of FRI Signals

https://github.com/vdeborto/cdsb

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Conditional Simulation Using Diffusion Schrödinger Bridges

https://github.com/vdutor/neural-diffusion-processes

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Neural Diffusion Processes

https://github.com/vibashan/tt-sfuda

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Target and Task specific Source-Free Domain Adaptive Image Segmentation

https://github.com/vibe007/Denoising_MC_Renders_Diffusion

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Denoising Monte Carlo Renders with Diffusion Models

https://github.com/vicliv/dte

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On Diffusion Modeling for Anomaly Detection

https://github.com/victorwz/zs-nmt-dae

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Rethinking Zero-shot Neural Machine Translation: From a Perspective of Latent Variables

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