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 421–430 of 1723 papers

TitleStatusHype
Exploring Scene Affinity for Semi-Supervised LiDAR Semantic SegmentationCode0
OpenScan: A Benchmark for Generalized Open-Vocabulary 3D Scene UnderstandingCode1
Near, far: Patch-ordering enhances vision foundation models' scene understanding—0
3D-Aware Instance Segmentation and Tracking in Egocentric Videos—0
SpectralGaussians: Semantic, spectral 3D Gaussian splatting for multi-spectral scene representation, visualization and analysis—0
SceneGPT: A Language Model for 3D Scene Understanding—0
HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors—0
Spherical World-Locking for Audio-Visual Localization in Egocentric Videos—0
DeepInteraction++: Multi-Modality Interaction for Autonomous DrivingCode3
Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D GaussianCode1
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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