Our formulation uses a novel Fourier object disentanglement method to innately separate out the human agent (which is typically small) from the background.
We present a novel architecture for 3D object detection, M3DeTR, which combines different point cloud representations (raw, voxels, bird-eye view) with different feature scales based on multi-scale feature pyramids.
Ranked #1 on 3D Object Detection on KITTI Cars Hard val
We interface GANav with a deep reinforcement learning-based navigation algorithm and highlight its benefits in terms of navigation in real-world unstructured terrains.
Ranked #1 on Semantic Segmentation on RELLIS-3D Dataset
In practice, our approach reduces the average prediction error by more than 54% over prior algorithms and achieves a weighted average accuracy of 91. 2% for behavior prediction.
Ranked #1 on Trajectory Prediction on ApolloScape