A new dataset with significant occlusions related to object manipulation.
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We present a large-scale dataset for 3D urban scene understanding. Compared to existing datasets, our dataset consists of 75 outdoor urban scenes with diverse backgrounds, encompassing over 15,000 images. These scenes offer 360◦ hemispherical views, capturing diverse foreground objects illuminated under various lighting conditions. Additionally, our dataset encompasses scenes that are not limited to forward-driving views, addressing the limitations of previous datasets such as limited overlap and coverage between camera views. The closest pre-existing dataset for generalizable evaluation is DTU [2] (80 scenes) which comprises mostly indoor objects and does not provide multiple foreground objects or background scenes.
3 PAPERS • 1 BENCHMARK
KITTI-6DoF is a dataset that contains annotations for the 6DoF estimation task for 5 object categories on 7,481 frames.
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Data and experiments for motion-based extrinsic calibration using trajectory_calibration. The data was generated for evaluating hand-eye calibration algorithms in extrinsic sensor-to-sensor calibration.