3 papers
cs.CV2026
DLTPose: 6DoF Pose Estimation From Accurate Dense Surface Point Estimates
Akash Jadhav, Michael Greenspan
We propose DLTPose, a novel method for 6DoF object pose estimation from RGBD images that combines the accuracy of sparse keypoint methods with the robustness of dense pixel-wise pr…
cs.CV2026
CollideNet: Hierarchical Multi-scale Video Representation Learning with Disentanglement for Time-To-Collision Forecasting
Nishq Poorav Desai, Ali Etemad, Michael Greenspan
Time-to-Collision (TTC) forecasting is a critical task in collision prevention, requiring precise temporal prediction and comprehending both local and global patterns encapsulated…
cs.CV2024
Pseudo-keypoint RKHS Learning for Self-supervised 6DoF Pose Estimation
Yangzheng Wu, Michael Greenspan
We address the simulation-to-real domain gap in six degree-of-freedom pose estimation (6DoF PE), and propose a novel self-supervised keypoint voting-based 6DoF PE framework, effect…