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 101–110 of 1723 papers

TitleStatusHype
Temporal Propagation of Asymmetric Feature Pyramid for Surgical Scene Segmentation—0
HAECcity: Open-Vocabulary Scene Understanding of City-Scale Point Clouds with Superpoint Graph Clustering—0
Training-Free Hierarchical Scene Understanding for Gaussian Splatting with Superpoint GraphsCode1
Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks—0
CAGS: Open-Vocabulary 3D Scene Understanding with Context-Aware Gaussian Splatting—0
DC-SAM: In-Context Segment Anything in Images and Videos via Dual ConsistencyCode1
Single-Input Multi-Output Model Merging: Leveraging Foundation Models for Dense Multi-Task Learning—0
Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization—0
SoccerNet-v3D: Leveraging Sports Broadcast Replays for 3D Scene UnderstandingCode1
FMLGS: Fast Multilevel Language Embedded Gaussians for Part-level Interactive Agents—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