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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/hulitaotom/Joint-Multi-Scale-Tone-Mapping-and-Denoising-for-HDR-Image-Enhancement

공식 코드

Joint Multi-Scale Tone Mapping and Denoising for HDR Image Enhancement

https://github.com/hunto/actgen

공식 코드

Active Generation for Image Classification

https://github.com/hunto/diffkd

공식 코드

Knowledge Diffusion for Distillation

https://github.com/hurunyi/videoshield

공식 코드

VideoShield: Regulating Diffusion-based Video Generation Models via Watermarking

https://github.com/hust-tan/diffusionvi

공식 코드

Diffusion Priors for Variational Likelihood Estimation and Image Denoising

https://github.com/hustvl/diffusiondrive

공식 코드

DiffusionDrive: Truncated Diffusion Model for End-to-End Autonomous Driving

https://github.com/hutaihang/faster-diffusion

공식 코드

Faster Diffusion: Rethinking the Role of the Encoder for Diffusion Model Inference

https://github.com/hyao1/glad

공식 코드

GLAD: Towards Better Reconstruction with Global and Local Adaptive Diffusion Models for Unsupervised Anomaly Detection

https://github.com/hyeonsoojo/metagc

공식 코드

Robust Graph Clustering via Meta Weighting for Noisy Graphs

https://github.com/hygenie1228/cycleadapt_release

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Cyclic Test-Time Adaptation on Monocular Video for 3D Human Mesh Reconstruction

https://github.com/hytidel/unetreweighting

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Dynamic Importance in Diffusion U-Net for Enhanced Image Synthesis

https://github.com/hzfinfdu/diffusion-bert

공식 코드

DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models

https://github.com/hzzone/du-gan

공식 코드

DU-GAN: Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising

https://github.com/ian-jihoonpark/X-Diffusion

공식 코드

Explaining generative diffusion models via visual analysis for interpretable decision-making process

https://github.com/ibm/baddiffusion

공식 코드

How to Backdoor Diffusion Models?

https://github.com/ibm/villandiffusion

공식 코드

VillanDiffusion: A Unified Backdoor Attack Framework for Diffusion Models

https://github.com/ibrahimethemhamamci/hierarchicaldet

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Diffusion-Based Hierarchical Multi-Label Object Detection to Analyze Panoramic Dental X-rays

https://github.com/icon-lab/SelfRDB

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Self-Consistent Recursive Diffusion Bridge for Medical Image Translation

https://github.com/icon-lab/denomamba

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DenoMamba: A fused state-space model for low-dose CT denoising

https://github.com/ictmcg/make-your-anchor

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Make-Your-Anchor: A Diffusion-based 2D Avatar Generation Framework

https://github.com/id-fr/idfr

공식 코드

Enhanced countering adversarial attacks via input denoising and feature restoring

https://github.com/idephics/diffsamp

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Sampling with flows, diffusion and autoregressive neural networks: A spin-glass perspective

https://github.com/idoamos/not-from-scratch

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Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors

https://github.com/idsia/fpainter

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Images as Weight Matrices: Sequential Image Generation Through Synaptic Learning Rules

https://github.com/ifryed/HyperRes

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Hypernetwork-Based Adaptive Image Restoration

https://github.com/igitugraz/weatherdiffusion

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Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models

https://github.com/iip-group/blind_and_nonparametric_estimators

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Low-Complexity Blind Parameter Estimation in Wireless Systems with Noisy Sparse Signals

https://github.com/iit-pavis/diffassemble

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DiffAssemble: A Unified Graph-Diffusion Model for 2D and 3D Reassembly

https://github.com/ilonafan/dar-noisy-labels

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Exploring Video-Based Driver Activity Recognition under Noisy Labels

https://github.com/imankhazrak/DDPM_X-Ray

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Addressing Small and Imbalanced Medical Image Datasets Using Generative Models: A Comparative Study of DDPM and PGGANs with Random and Greedy K Sampling

https://github.com/imlixinyang/director3d

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Director3D: Real-world Camera Trajectory and 3D Scene Generation from Text

https://github.com/inbarhub/ddpm_inversion

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An Edit Friendly DDPM Noise Space: Inversion and Manipulations

https://github.com/inceturker/blind-restoration-of-real-world-audio-by-1d-operational-gans

공식 코드

Blind Restoration of Real-World Audio by 1D Operational GANs

https://github.com/indigopurple/mag

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Point Cloud Denoising via Momentum Ascent in Gradient Fields

https://github.com/indigopurple/manet

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MANet: Improving Video Denoising with a Multi-Alignment Network

https://github.com/indu1ge/DepthMaster

공식 코드

DepthMaster: Taming Diffusion Models for Monocular Depth Estimation

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