In this paper, we propose a simple yet effective approach for Tracking Any Point with
TRansformers (TAPTR). Based on the observation that point tracking bears a great …

Semantic scene completion also known as semantic occupancy prediction can provide
dense geometric and semantic information for autonomous vehicles which attracts the …

Semantic scene completion (SSC) aims to predict the semantic occupancy of each voxel in
the entire 3D scene from limited observations, which is an emerging and critical task for …

Vision-based Semantic Scene Completion (SSC) has gained much attention due to its
widespread applications in various 3D perception tasks. Existing sparse-to-dense …

Abstract Camera-based Semantic Scene Completion (SSC) is to infer the full geometry of
objects and scenes from only 2D images. The task is particularly challenging for those …

We study outdoor 3D scene understanding, a challenging task demanding the intelligent
system to infer both geometry and semantics from a single-view image–a critical skill for …

Semantic scene completion (SSC) aims to simultaneously perform scene completion (SC)
and predict semantic categories of a 3D scene from a single depth and/or RGB image. Most …

In recent years, autonomous driving has garnered escalating attention for its potential to
relieve drivers' burdens and improve driving safety. Vision-based 3D occupancy prediction …

Traditional image coding standards are typically optimized with a focus on human
perception, which conflicts with the fact that most of the images are now analyzed by …

Predicting per-voxel occupancy status and corresponding semantic labels in 3D scenes is
pivotal to 3D intelligent perception in autonomous driving. In this paper, we propose a novel …