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 81–90 of 1723 papers

TitleStatusHype
BinsFormer: Revisiting Adaptive Bins for Monocular Depth EstimationCode2
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene UnderstandingCode2
EmbodiedOcc: Embodied 3D Occupancy Prediction for Vision-based Online Scene UnderstandingCode2
PLA: Language-Driven Open-Vocabulary 3D Scene UnderstandingCode2
Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene UnderstandingCode2
LSceneLLM: Enhancing Large 3D Scene Understanding Using Adaptive Visual PreferencesCode2
Chameleon: Fast-slow Neuro-symbolic Lane Topology ExtractionCode2
Chat-Scene: Bridging 3D Scene and Large Language Models with Object IdentifiersCode2
Feed-Forward SceneDINO for Unsupervised Semantic Scene CompletionCode2
ARKit LabelMaker: A New Scale for Indoor 3D Scene UnderstandingCode2
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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