6 citations · 14 across the 8 of their papers we have counts for
4 papers · 1 filter
BlendCLIP: Bridging Synthetic and Real Domains for Zero-Shot 3D Object Classification with Multimodal Pretraining
Ajinkya Khoche, Gergő László Nagy, Maciej Wozniak +2
Zero-shot 3D object classification is crucial for real-world applications like autonomous driving, however it is often hindered by a significant domain gap between the synthetic da…
DoGFlow: Self-Supervised LiDAR Scene Flow via Cross-Modal Doppler Guidance
Ajinkya Khoche, Qingwen Zhang, Yixi Cai +2
Accurate 3D scene flow estimation is critical for autonomous systems to navigate dynamic environments safely, but creating the necessary large-scale, manually annotated datasets re…
HiMo: High-Speed Objects Motion Compensation in Point Clouds
Qingwen Zhang, Ajinkya Khoche, Yi Yang +4
LiDAR point cloud is essential for autonomous vehicles, but motion distortions from dynamic objects degrade the data quality. While previous work has considered distortions caused…
SSF: Sparse Long-Range Scene Flow for Autonomous Driving
Ajinkya Khoche, Qingwen Zhang, Laura Pereira Sanchez +3
Scene flow enables an understanding of the motion characteristics of the environment in the 3D world. It gains particular significance in the long-range, where object-based percept…