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 511–520 of 1723 papers

TitleStatusHype
OpenESS: Event-based Semantic Scene Understanding with Open VocabulariesCode2
Multi-Modal Data-Efficient 3D Scene Understanding for Autonomous DrivingCode3
DriveWorld: 4D Pre-trained Scene Understanding via World Models for Autonomous Driving—0
Q-GroundCAM: Quantifying Grounding in Vision Language Models via GradCAM—0
Seeing Beyond Classes: Zero-Shot Grounded Situation Recognition via Language Explainer—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
On Support Relations Inference and Scene Hierarchy Graph Construction from Point Cloud in Clustered Environments—0
BACS: Background Aware Continual Semantic SegmentationCode0
Unified Scene Representation and Reconstruction for 3D Large Language Models—0
SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth EstimationCode2
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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