3 accepted papers
LiDAR-based 3D detection methods currently use bird's-eye view (BEV) or range view (RV) as their primary basis. The former relies on voxelization and 3D convolutions, resulting in inefficient training and inference processes. Conversely, RV-based methods demonstrate higher efficiency due to their co…
Point-, voxel-, and range-views are three representative forms of point clouds. All of them have accurate 3D measurements but lack color and texture information. RGB images are a natural complement to these point cloud views and fully utilizing the comprehensive information of them benefits more rob…
Despite some exciting progress on high-quality image generation from structured (scene graphs) or free-form (sentences) descriptions, most of them only guarantee the image-level semantical consistency, i.e. the generated image matching the semantic meaning of the description. They still lack the inv…