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Image Reconstruction On Imagenet

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FID
LPIPS
PSNR
SSIM

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname
FID
LPIPS
PSNR
SSIM
Paper TitleRepository
Taming-VQGAN (16x16)3.640.17719.930.542Taming Transformers for High-Resolution Image Synthesis-
Open-Magvit2 (16x16)1.17-21.90-Open-MAGVIT2: An Open-Source Project Toward Democratizing Auto-regressive Visual Generation-
TiTok-S-1281.71---An Image is Worth 32 Tokens for Reconstruction and Generation-
VQGAN-LC (16x16)2.620.12023.800.589Scaling the Codebook Size of VQGAN to 100,000 with a Utilization Rate of 99%-
OptVQ (16x16x8)0.910.06627.570.729Preventing Local Pitfalls in Vector Quantization via Optimal Transport-
MaskBit (16x16)1.66---MaskBit: Embedding-free Image Generation via Bit Tokens-
IBQ (16x16)1.000.2030--Scalable Image Tokenization with Index Backpropagation Quantization-
ViT-VQGAN (16x16)1.28---Vector-quantized Image Modeling with Improved VQGAN-
MaskGIT-VQGAN (16x16)2.28---MaskGIT: Masked Generative Image Transformer-
RQ-VAE (8x8x16)1.83---Autoregressive Image Generation using Residual Quantization-
OptVQ (16x16x4)1.000.07626.590.717Preventing Local Pitfalls in Vector Quantization via Optimal Transport-
Mo-VQGAN (16x16x4)1.120.11322.420.673MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation-
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Image Reconstruction On Imagenet | SOTA | HyperAI