3D Semantic Scene Completion
25 papers with code • 4 benchmarks • 5 datasets
This task was introduced in "Semantic Scene Completion from a Single Depth Image" (https://arxiv.org/abs/1611.08974) at CVPR 2017 . The target is to infer the dense 3D voxelized semantic scene from an incompleted 3D input (e.g. point cloud, depth map) and an optional RGB image. A recent summary can be found in the paper "3D Semantic Scene Completion: a Survey" (https://arxiv.org/abs/2103.07466), published at IJCV 2021.
NYUv2
SemanticKITTI
KITTI-360
PRO-teXt
SSCBench
Most implemented papers
Semantic Scene Completion from a Single Depth Image
This paper focuses on semantic scene completion, a task for producing a complete 3D voxel representation of volumetric occupancy and semantic labels for a scene from a single-view depth map observation.
3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior
charlesCXK/3D-SketchAware-SSC
•
•
CVPR 2020
To this end, we first propose a novel 3D sketch-aware feature embedding to explicitly encode geometric information effectively and efficiently.
LMSCNet: Lightweight Multiscale 3D Semantic Completion
cv-rits/LMSCNet
•
•
We introduce a new approach for multiscale 3Dsemantic scene completion from voxelized sparse 3D LiDAR scans.
SCFusion: Real-time Incremental Scene Reconstruction with Semantic Completion
We propose a framework that ameliorates this issue by performing scene reconstruction and semantic scene completion jointly in an incremental and real-time manner, based on an input sequence of depth maps.
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion
yanx27/JS3C-Net
•
•
In practice, an initial semantic segmentation (SS) of a single sweep point cloud can be achieved by any appealing network and then flows into the semantic scene completion (SSC) module as the input.
Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction
wzzheng/tpvformer
•
•
CVPR 2023
To lift image features to the 3D TPV space, we further propose a transformer-based TPV encoder (TPVFormer) to obtain the TPV features effectively.
See and Think: Disentangling Semantic Scene Completion
ShiceLiu/SATNet
•
•
NeurIPS 2018
Semantic scene completion predicts volumetric occupancy and object category of a 3D scene, which helps intelligent agents to understand and interact with the surroundings.
Efficient Semantic Scene Completion Network with Spatial Group Convolution
zjhthu/SGC-Release
•
•
ECCV 2018
We introduce Spatial Group Convolution (SGC) for accelerating the computation of 3D dense prediction tasks.
EdgeNet: Semantic Scene Completion from a Single RGB-D Image
Semantic scene completion is the task of predicting a complete 3D representation of volumetric occupancy with corresponding semantic labels for a scene from a single point of view.
Anisotropic Convolutional Networks for 3D Semantic Scene Completion
In contrast to the standard 3D convolution that is limited to a fixed 3D receptive field, our module is capable of modeling the dimensional anisotropy voxel-wisely.
