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 1111–1120 of 1723 papers

TitleStatusHype
Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and TrackingCode2
Improving Building Segmentation for Off-Nadir Satellite Imagery—0
Binaural SoundNet: Predicting Semantics, Depth and Motion with Binaural Sounds—0
Spatio-temporal Self-Supervised Representation Learning for 3D Point CloudsCode1
From General to Specific: Informative Scene Graph Generation via Balance AdjustmentCode1
Multi-task learning from fixed-wing UAV images for 2D/3D city modeling—0
DeepPanoContext: Panoramic 3D Scene Understanding with Holistic Scene Context Graph and Relation-based OptimizationCode1
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks—0
ODAM: Object Detection, Association, and Mapping using Posed RGB VideoCode1
A Multiple-View Geometric Model for Specularity Prediction on General Curved Surfaces—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