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 561–570 of 1723 papers

TitleStatusHype
Are Vision LLMs Road-Ready? A Comprehensive Benchmark for Safety-Critical Driving Video UnderstandingCode0
Vision-Centric Representation-Efficient Fine-Tuning for Robust Universal Foreground Segmentation—0
Temporal Propagation of Asymmetric Feature Pyramid for Surgical Scene Segmentation—0
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene UnderstandingCode0
HAECcity: Open-Vocabulary Scene Understanding of City-Scale Point Clouds with Superpoint Graph Clustering—0
Explainable Scene Understanding with Qualitative Representations and Graph Neural Networks—0
CAGS: Open-Vocabulary 3D Scene Understanding with Context-Aware Gaussian Splatting—0
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
DSM: Building A Diverse Semantic Map for 3D Visual Grounding—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