Scene flow characterizes the 3D motion between two LiDAR scans captured by an
autonomous vehicle at nearby timesteps. Prevalent methods consider scene flow as point …

Learning 3D scene flow from LiDAR point clouds presents significant difficulties including
poor generalization from synthetic datasets to real scenes scarcity of real-world 3D labels …

Scene flow estimation predicts the 3D motion at each point in successive LiDAR scans. This
detailed, point-level, information can help autonomous vehicles to accurately predict and …

In contrast to current state-of-the-art methods, such as NSFP [25], which employ deep
implicit neural functions for modeling scene flow, we present a novel approach that utilizes …

We reframe scene flow as the task of estimating a continuous space-time ordinary
differential equation (ODE) that describes motion for an entire observation sequence …

We reframe scene flow as the task of estimating a continuous space-time ODE that
describes motion for an entire observation sequence, represented with a neural prior. Our …

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 perception …

Integrace technologiı́ 3D počı́tačového viděnı́, zejména bodových mraků LiDARu (Light
Detection and Ranging), zásadnı́m způsobem revolucionizovala oblasti jako je autonomnı́ …

Integrace technologiı́ 3D počı́tačového viděnı́, zejména bodových mraků LiDARu (Light
Detection and Ranging), zásadnı́m způsobem revolucionizovala oblasti jako je autonomnı́ …