Arbitrary-Scale Image Generation and Upsampling Using Latent Diffusion Model and Implicit Neural Decoder
Jinseok Kim, Tae-Kyun Kim
2024年份
9顶会引用
摘要
Resolution (a) Arbitrary-Scale Image Generation Figure 1. The proposed method generates novel images and super-resolves low-resolution images at arbitrary-scales with high fidelity, diversity, and fast inference speed.
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引用它的顶会 Paper9
- Exploit Your Latents: Coarse-Grained Protein Backmapping with Latent Diffusion ModelsRongchao Zhang, Yu Huang, Yiwei Lou, Yi Xin 等AAAI 2025 · 被引用 7 次
- SASNet: Spatially-Adaptive Sinusoidal Networks for INRsHaoan Feng, Diana Aldana, Tiago Novello, Leila De FlorianiCVPR 2026 · 被引用 4 次
- Diffusion Transformer Meets Multi-Level Wavelet Spectrum for Single Image Super-ResolutionPeng Du, Hui Li, Han Xu, Paul Barom Jeon 等ICCV 2025 · 被引用 3 次
- SRHand: Super-Resolving Hand Images and 3D Shapes via View/Pose-aware Neural Image Representations and Explicit MeshesMinje Kim, Tae-Kyun KimNeurIPS 2025 · 被引用 2 次
- CASR: A Robust Cyclic Framework for Arbitrary Large-Scale Super-Resolution with Distribution Alignment and Self-Similarity AwarenessWenhao Guo, Zhaoran Zhao, Peng Lu, Sheng Li 等CVPR 2026 · 被引用 1 次
它引用的顶会 Paper19
- Denoising Diffusion Probabilistic ModelsJonathan Ho, Ajay Jain, Pieter AbbeelNeurIPS 2020 · 被引用 35,902 次
- High-Resolution Image Synthesis with Latent Diffusion ModelsRobin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser 等CVPR 2022 · 被引用 13,123 次
- Denoising Diffusion Implicit ModelsJiaming Song, Chenlin Meng, Stefano ErmonICLR 2021 · 被引用 11,743 次
- MultiDiffusion: Fusing Diffusion Paths for Controlled Image GenerationOmer Bar-Tal, Lior Yariv, Yaron Lipman, Tali DekelICML 2023 · 被引用 575 次
- DiffusionCLIP: Text-Guided Diffusion Models for Robust Image ManipulationGwanghyun Kim, Taesung Kwon, Jong Chul YeCVPR 2022 · 被引用 458 次
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