26 datasets found

The PASCAL VOC2012 dataset is a benchmark for object detection, containing 1464 images with corresponding labeled object instances for 20 classes.

The KITTI benchmark dataset is used to evaluate the performance of the proposed method. The dataset contains large-scale outdoor sequences of images captured by a forward-facing...

Occupancy prediction plays a pivotal role in au-

The MIT-Adobe FiveK dataset, a large-scale dataset for image segmentation and object detection.

Person search unifies person detection and person re-identification (Re-ID) to locate query persons from the panoramic gallery images. One major challenge comes from the...

CUHK-SYSU is a large-scale dataset designed for person search, which contains 18,184 scene images captured from street nap and movie screenshot.

The dataset used in the paper is a video prediction dataset with occlusions, which is used to evaluate the proposed Fast Fourier Inception Networks (FFINet) for occluded video...

The PASCAL VOC dataset contains 20 classes, including person, animal, vehicle, and indoor, with 9,963 images containing 24,640 annotated objects.

The dataset used in the paper is the Swin-B dataset, a variant of the Swin Transformer model.

The MS COCO dataset is a large benchmark for image captioning, containing 328K images with 5 caption descriptions each.

The ImageNet dataset is a large-scale image database that contains over 14 million images, each labeled with one of 21,841 categories.

The dataset used in this paper is a collection of frames for video coding, with different Quantisation Parameters (QPs) and frame types.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the OpenImages dataset to train their models.

KITTI 2012 is a real-world dataset in the outdoor scenario, and contains 194 training and 195 testing stereo image pairs with the size of 376 × 1240.

The CARLA dataset is a complex urban-like environment with multi-agent dynamics, pedestrians, intersections, cross-traffic, roundabout, and changing weather conditions.

The dataset used in the paper is MS COCO2017, a large-scale object detection dataset.

Multi-label image recognition is a practical and challenging task compared to single-label image classification.

The KITTI Vision Benchmark Suite is a dataset used for object detection and tracking in autonomous vehicles.

Object detection is one of the most foundational computer vision task and is essential for many real-world applications. The object detection pipeline has been developed...

Object recognition is arguably the most important problem at the heart of computer vision. Recently, Barbu et al. introduced a dataset called ObjectNet which includes objects in...