11 datasets found

The dataset used in the paper is ImageNet-1k and ImageNet-100, which are large-scale image classification datasets.

The dataset used in the paper is the VOC dataset, which is a dataset for object detection and segmentation.

The dataset used in the paper is ImageNet V2, a large-scale image classification dataset.

SODA10M contains 10M un-labeled images and 20K labeled images of size 1920 × 1080 with default format of JPEG.

Youtube-8M is a large-scale video classification benchmark.

The dataset used in the paper SpikingNeRF: Making Bio-inspired Neural Networks See through the Real World

The dataset used in the paper is VGGFace2, which is a dataset for face recognition tasks.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...

A benchmark for low-shot recognition was proposed by Hariharan & Girshick (2017) and consists of a representation learning phase without access to the low-shot classes and a...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used it for language modeling and image classification tasks.

Large scale datasets [18, 17, 27, 6] boosted text conditional image generation quality. However, in some domains it could be difficult to make such datasets and usually it could...