13 datasets found

The BabyYoda dataset includes up to 150 unique distractors, with controlled lighting and precise object placement.

The Android dataset includes two Android robot figures with three small wooden robots as distractors.

The Statue dataset includes a small statue on a decorative box with a balloon as a persistent distractor.

The RobustNeRF dataset includes several scenes with various distractors, captured in different settings.

Neural radiance fields (NeRF) excel at synthesizing new views given multi-view, calibrated images of a static scene. When scenes include distractors, which are not persistent...

Agricultural robotics dataset for panoptic 3D scene understanding

A large-scale dataset of indoor 3D scenes with semantic annotations.

BDD100K Dataset is a large-scale dataset for autonomous driving, containing 100,000 images, with 20,000 images for training and 80,000 images for testing.

The authors used the RefCOCO dataset, a large-scale dataset for object detection and scene understanding, to train and evaluate their models.

The dataset used in the paper is the NuScenes dataset, which contains LiDAR point clouds and corresponding semantic annotations.

The Replica dataset contains 18 various highly photo-realistic indoor environments. It provides dense-mesh, high-resolution RGBD images and a large range of instance annotations...

The dataset used in the paper is the KITTI dataset, which is a benchmark for monocular depth estimation. The dataset consists of a large collection of images and corresponding...

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...