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 1381–1390 of 1723 papers

TitleStatusHype
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation—0
AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted SurgeryCode0
Cross-modal Learning for Multi-modal Video Categorization—0
An Evaluation of Knowledge Graph Embeddings for Autonomous Driving Data: Experience and Practice—0
Shallow2Deep: Indoor Scene Modeling by Single Image Understanding—0
3D Gated Recurrent Fusion for Semantic Scene Completion—0
Exploiting Temporal Coherence for Multi-modal Video Categorization—0
PoSeg: Pose-Aware Refinement Network for Human Instance Segmentation—0
Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation—0
Multi-Modal Attention-based Fusion Model for Semantic Segmentation of RGB-Depth Images—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