Nov 3, 2022 · Equipped with ImageNet-X, we investigate 2,200 current recognition models and study the types of mistakes as a function of model's (1) ...

IMAGENET-X: UNDERSTANDING MODEL MISTAKES. WITH FACTOR OF VARIATION ANNOTATIONS. Badr Youbi Idrissi, Diane Bouchacourt, Randall Balestriero, Ivan Evtimov ...

Oct 31, 2023 · ImagenetX : Understanding model mistakes with factors of variation annotations. Code to load annotations, evaluate models and reproduce paper plots.

Nov 3, 2022 · A set of sixteen human annotations of factors such as pose, background, or lighting the entire ImageNet-1k validation set as well as a random subset of 12k ...

Nov 3, 2022 · We introduce ImageNet-X, a set of sixteen human annotations of factors such as pose, background, or lighting the entire ImageNet-1k validation set.

ImageNet-X is a set of human annotations pinpointing failure types for the popular ImageNet dataset. ImageNet-X labels distinguishing object factors.

Imagenet-x: Understanding model mistakes with factor of variation annotations. Idrissi, B. Y., Bouchacourt, D., Balestriero, R., Evtimov, I., Hazirbas, C., ...

Explore all code implementations available for ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations.

ImageNet-X is a dataset that extends ImageNet-1K with detailed human annotations for 16 factors of variation, enabling an in-depth analysis of model mistakes ...

Nov 4, 2022 · ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations abs: https://arxiv.org/abs/2211.01866 project page: ...