“ImageNet 512x512” refers to the ImageNet ILSVRC-2012 (ImageNet-1k) image classification dataset commonly used for research, where the original images are redistributed or preprocessed (resized / center-cropped) to 512×512 resolution for training or evaluation of generative and conditional models. ImageNet ILSVRC-2012 contains 1,281,167 training images across 1000 classes and 50,000 validation images (50 images per class), which is why many generative-model papers report FID / Inception Score using 50,000 generated samples (often 50 samples per class) and compute scores against the ImageNet training/validation sets. Core references: the dataset introduction (Deng et al., CVPR 2009) and the ImageNet Large Scale Visual Recognition Challenge paper (Russakovsky et al., arXiv:1409.0575). Official dataset info and download/size counts are listed on the ImageNet site; a Hugging Face repack of the ILSVRC/imagenet-1k dataset is available at the linked HF repo.
No results indexed yet — be the first to submit a score.
Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.