3D Semantic Scene Completion from a single RGB image
9 papers with code • 3 benchmarks • 4 datasets
This task relies on a single RGB image to infer the dense 3D voxelized semantic scene.
Benchmarks
These leaderboards are used to track progress in 3D Semantic Scene Completion from a single RGB image
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NYUv2
SemanticKITTI
KITTI-360
SSCBench
Most implemented papers
3D Sketch-aware Semantic Scene Completion via Semi-supervised Structure Prior
charlesCXK/3D-SketchAware-SSC
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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
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We introduce a new approach for multiscale 3Dsemantic scene completion from voxelized sparse 3D LiDAR scans.
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion
yanx27/JS3C-Net
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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.
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.
MonoScene: Monocular 3D Semantic Scene Completion
cv-rits/MonoScene
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CVPR 2022
MonoScene proposes a 3D Semantic Scene Completion (SSC) framework, where the dense geometry and semantics of a scene are inferred from a single monocular RGB image.
VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion
nvlabs/voxformer
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CVPR 2023
To enable such capability in AI systems, we propose VoxFormer, a Transformer-based semantic scene completion framework that can output complete 3D volumetric semantics from only 2D images.
OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction
zhangyp15/occformer
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ICCV 2023
The vision-based perception for autonomous driving has undergone a transformation from the bird-eye-view (BEV) representations to the 3D semantic occupancy.
Symphonize 3D Semantic Scene Completion with Contextual Instance Queries
`3D Semantic Scene Completion (SSC) has emerged as a nascent and pivotal undertaking in autonomous driving, aiming to predict voxel occupancy within volumetric scenes.
NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Space
Jiawei-Yao0812/NDCScene
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ICCV 2023
Monocular 3D Semantic Scene Completion (SSC) has garnered significant attention in recent years due to its potential to predict complex semantics and geometry shapes from a single image, requiring no 3D inputs.
