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 1041–1050 of 1723 papers

TitleStatusHype
Transavs: End-To-End Audio-Visual Segmentation With Transformer—0
HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
HGS-Mapping: Online Dense Mapping Using Hybrid Gaussian Representation in Urban Scenes—0
Hierarchical Scene Parsing by Weakly Supervised Learning with Image Descriptions—0
Hierarchy Denoising Recursive Autoencoders for 3D Scene Layout Prediction—0
High-Accuracy Facial Depth Models derived from 3D Synthetic Data—0
Highway Driving Dataset for Semantic Video Segmentation—0
HIS-GPT: Towards 3D Human-In-Scene Multimodal Understanding—0
HOIverse: A Synthetic Scene Graph Dataset With Human Object Interactions—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