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 981–990 of 1723 papers

TitleStatusHype
Recent Advances in Multi-modal 3D Scene Understanding: A Comprehensive Survey and Evaluation—0
P2AT: Pyramid Pooling Axial Transformer for Real-time Semantic SegmentationCode0
Panoptic Out-of-Distribution Segmentation—0
S4C: Self-Supervised Semantic Scene Completion with Neural Fields—0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models—0
TextPSG: Panoptic Scene Graph Generation from Textual Descriptions—0
DualMLP: a two-stream fusion model for 3D point cloud classificationCode0
Adaptive Visual Scene Understanding: Incremental Scene Graph GenerationCode0
Elastic Interaction Energy-Informed Real-Time Traffic Scene Perception—0
Logical Bias Learning for Object Relation Prediction—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