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.

Most implemented papers

Semantic Scene Completion from a Single Depth Image

shurans/sscnet CVPR 2017

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 24 Aug 2020

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

ShunChengWu/SCFusion 26 Oct 2020

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 7 Dec 2020

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

UnBVision/edgenet 8 Aug 2019

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

waterljwant/SSC CVPR 2020

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.