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 571–580 of 1723 papers

TitleStatusHype
Application of Multimodal Large Language Models in Autonomous Driving—0
DEF-oriCORN: efficient 3D scene understanding for robust language-directed manipulation without demonstrations—0
Hybrid Memoised Wake-Sleep: Approximate Inference at the Discrete-Continuous Interface—0
Hybrid Optimized Deep Convolution Neural Network based Learning Model for Object Detection—0
DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM—0
Trajectory-based Scene Understanding using Dirichlet Process Mixture Model—0
BUTLER: Building Understanding in TextWorld via Language for Embodied Reasoning—0
Dynamic Scene Understanding from Vision-Language Representations—0
Building an Affordances Map with Interactive Perception—0
A pooling based scene text proposal technique for scene text reading in the wild—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