ImageNet-21K dataset, which contains more pictures and classes, is used less frequently for pretraining, mainly due to its complexity, and underestimation of its added value compared to …

2025年3月17日 · In this work, we conduct a comprehensive analysis of the impact of various thinking types on model performance and introduce ThinkPatterns-21k, a curated dataset …

Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. The **ImageNet** dataset contains 14,197,122 annotated images …

2021年4月22日 · This paper aims to close this gap, and make high-quality efficient pretraining on ImageNet-21K available for everyone. Via a dedicated preprocessing stage, utilization of …

2021年4月22日 · We also show that we outperform previous ImageNet-21K pretraining schemes for prominent new models like ViT and Mixer. Our proposed pretraining pipeline is efficient, …

Vision Transformer (ViT): Implementation of the Vision Transformer, a cutting-edge model designed to leverage the large and diverse ImageNet-21K dataset for state-of-the-art …

The current state-of-the-art on ImageNet-21k is POMP. See a full comparison of 2 papers with code.

2021年7月29日 · ImageNet-21K dataset, which is bigger and more diverse, is used less frequently for pretraining, mainly due to its complexity, low accessibility, and underestimation of its added …

2021年1月8日 · ImageNet-21K dataset, which contains more pictures and classes, is used less frequently for pretraining, mainly due to its complexity, and underestimation of its added value …

ImageNet-21K dataset, which contains more pictures and classes, is used less frequently for pretraining, mainly due to its complexity, and underestimation of its added value compared to …