SOTAVerified

Scene Understanding

Scene understanding involves interpreting the visual information of a scene, including objects, their spatial relationships, and the overall layout. It goes beyond simple object recognition by considering the context and how objects relate to each other and the environment.

Papers

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Showing 841–850 of 1723 papers

TitleStatusHype
ESGNN: Towards Equivariant Scene Graph Neural Network for 3D Scene Understanding—0
EgoGaussian: Dynamic Scene Understanding from Egocentric Video with 3D Gaussian Splatting—0
PPTFormer: Pseudo Multi-Perspective Transformer for UAV Segmentation—0
3D-MVP: 3D Multiview Pretraining for Robotic Manipulation—0
GPT-4V Explorations: Mining Autonomous Driving—0
EvSegSNN: Neuromorphic Semantic Segmentation for Event Data—0
Enhancing Generalizability of Representation Learning for Data-Efficient 3D Scene Understanding—0
DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features—0
MapVision: CVPR 2024 Autonomous Grand Challenge Mapless Driving Tech Report—0
Category-level Neural Field for Reconstruction of Partially Observed Objects in Indoor EnvironmentCode0
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All datasetsSemantic Scene Understanding Challenge (passive actuation & ground-truth localisation)ADE20K valSemantic Scene Understanding Challenge (active actuation & ground-truth localisation)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.44—Unverified
2Team VGAI (TCS Research)OMQ0.37—Unverified
3Demo_semantic_SLAMOMQ0.11—Unverified
#ModelMetricClaimedVerifiedStatus
1CPN(ResNet-101)Mean IoU46.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ACRV BaselineOMQ0.35—Unverified