Attention mechanisms in computer vision: A survey
Humans can naturally and effectively find salient regions in complex scenes. Motivated by
this observation, attention mechanisms were introduced into computer vision with the aim of …
this observation, attention mechanisms were introduced into computer vision with the aim of …
Unsupervised point cloud representation learning with deep neural networks: A survey
Point cloud data have been widely explored due to its superior accuracy and robustness
under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved …
under various adverse situations. Meanwhile, deep neural networks (DNNs) have achieved …
Snowflakenet: Point cloud completion by snowflake point deconvolution with skip-transformer
Point cloud completion aims to predict a complete shape in high accuracy from its partial
observation. However, previous methods usually suffered from discrete nature of point cloud …
observation. However, previous methods usually suffered from discrete nature of point cloud …
Pmp-net: Point cloud completion by learning multi-step point moving paths
The task of point cloud completion aims to predict the missing part for an incomplete 3D
shape. A widely used strategy is to generate a complete point cloud from the incomplete …
shape. A widely used strategy is to generate a complete point cloud from the incomplete …
Pmp-net++: Point cloud completion by transformer-enhanced multi-step point moving paths
Point cloud completion concerns to predict missing part for incomplete 3D shapes. A
common strategy is to generate complete shape according to incomplete input. However …
common strategy is to generate complete shape according to incomplete input. However …
Point cloud completion by skip-attention network with hierarchical folding
Point cloud completion aims to infer the complete geometries for missing regions of 3D
objects from incomplete ones. Previous methods usually predict the complete point cloud …
objects from incomplete ones. Previous methods usually predict the complete point cloud …
Learning a more continuous zero level set in unsigned distance fields through level set projection
Latest methods represent shapes with open surfaces using unsigned distance functions
(UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the …
(UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the …
Geometric back-projection network for point cloud classification
As the basic task of point cloud analysis, classification is fundamental but always
challenging. To address some unsolved problems of existing methods, we propose a …
challenging. To address some unsolved problems of existing methods, we propose a …
M3detr: Multi-representation, multi-scale, mutual-relation 3d object detection with transformers
We present a novel architecture for 3D object detection, M3DETR, which combines different
point cloud representations (raw, voxels, bird-eye view) with different feature scales based …
point cloud representations (raw, voxels, bird-eye view) with different feature scales based …
Cycle4completion: Unpaired point cloud completion using cycle transformation with missing region coding
In this paper, we present a novel unpaired point cloud completion network, named
Cycle4Completion, to infer the complete geometries from a partial 3D object. Previous …
Cycle4Completion, to infer the complete geometries from a partial 3D object. Previous …