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 271–280 of 1723 papers

TitleStatusHype
Embodied VideoAgent: Persistent Memory from Egocentric Videos and Embodied Sensors Enables Dynamic Scene Understanding—0
OVGaussian: Generalizable 3D Gaussian Segmentation with Open VocabulariesCode0
Text-to-Image GAN with Pretrained Representations—0
4D Gaussian Splatting: Modeling Dynamic Scenes with Native 4D Primitives—0
MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic ScenariosCode0
UniPLV: Towards Label-Efficient Open-World 3D Scene Understanding by Regional Visual Language Supervision—0
Parallel Neural Computing for Scene Understanding from LiDAR Perception in Autonomous RacingCode0
3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene UnderstandingCode2
LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding—0
Application of Multimodal Large Language Models in Autonomous Driving—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