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 911–920 of 1723 papers

TitleStatusHype
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples—0
Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse WeatherCode0
Computational Imaging for Machine Perception: Transferring Semantic Segmentation beyond AberrationsCode0
Object-level 3D Semantic Mapping using a Network of Smart Edge Sensors—0
An Enhanced Object Detection Model for Scene Graph Generation—0
BEVDistill: Cross-Modal BEV Distillation for Multi-View 3D Object DetectionCode1
FlowGrad: Using Motion for Visual Sound Source LocalizationCode0
Monocular BEV Perception of Road Scenes via Front-to-Top View Projection—0
Visually Grounded VQA by Lattice-based RetrievalCode0
User Identification: A Key Enabler for Multi-User Vision-Aided Communications—0
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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