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 1241–1250 of 1723 papers

TitleStatusHype
Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion—0
Robust Category-Level 3D Pose Estimation from Synthetic Data—0
Robust deep learning-based semantic organ segmentation in hyperspectral images—0
Robust Multi-Modal Image Stitching for Improved Scene Understanding—0
CAGS: Open-Vocabulary 3D Scene Understanding with Context-Aware Gaussian Splatting—0
Robust Visual Localization via Semantic-Guided Multi-Scale Transformer—0
Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms—0
CaDIS: Cataract Dataset for Image Segmentation—0
Ross3D: Reconstructive Visual Instruction Tuning with 3D-Awareness—0
3D-RCNN: Instance-Level 3D Object Reconstruction via Render-and-Compare—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