Omkar2118/datasets huggingface dataset:
ARKitTrack

**ARKitTrack** is a new RGB-D tracking dataset for both static and dynamic scenes captured by consumer-grade LiDAR scanners equipped on Apple's iPhone and iPad. ARKitTrack contains 300 RGBD sequences, 455 targets, and 229.7K video frames in total. This dataset has 123.9K pixel-level target masks along with the bounding box annotations and frame-level attributes.

Source: [ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data](https://arxiv.org/pdf/2303.13885v1.pdf)

Image Source: [ARKitTrack: A New Diverse Dataset for Tracking Using Mobile RGB-D Data](https://arxiv.org/pdf/2303.13885v1.pdf)
HAMMER

**HAMMER** dataset contains 13 Scenes. Each scene has two setups, with/without objects (with : scene includes several objects with various surface material, without : scene with only backgrounds - naked) and each scene has two camera trajectories. Each trajectories composed with roughly 300 frames, which adds up to 16k frames in total (13 x 2 x 2 x 300). Each trajectory contains corresponding images from each cameras : d435 – stereo, l515 – Lidar (D-ToF), polarization – RGBP (RGB with polarization), tof – (I-ToF). Each camera folder contains its intrinsic file and its own recorded images together with rendered depth GT / instance GT and camera pose. All the cameras are fully synchronized via robotic arm’s data acquisition setup.

Source: [On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks](https://arxiv.org/pdf/2303.14840v1.pdf)

Image Source: [On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks](https://arxiv.org/pdf/2303.14840v1.pdf)

Introducing paper: On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks