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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 111–120 of 1723 papers

TitleStatusHype
DSM: Building A Diverse Semantic Map for 3D Visual Grounding—0
FMLGS: Fast Multilevel Language Embedded Gaussians for Part-level Interactive Agents—0
DGOcc: Depth-aware Global Query-based Network for Monocular 3D Occupancy Prediction—0
Masked Scene Modeling: Narrowing the Gap Between Supervised and Self-Supervised Learning in 3D Scene UnderstandingCode1
MovSAM: A Single-image Moving Object Segmentation Framework Based on Deep ThinkingCode0
RayFronts: Open-Set Semantic Ray Frontiers for Online Scene Understanding and Exploration—0
Audio-visual Event Localization on Portrait Mode Short Videos—0
Attributes-aware Visual Emotion Representation Learning—0
PRIMEDrive-CoT: A Precognitive Chain-of-Thought Framework for Uncertainty-Aware Object Interaction in Driving Scene Scenario—0
CamContextI2V: Context-aware Controllable Video GenerationCode1
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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