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 1221–1230 of 1723 papers

TitleStatusHype
DiffSDFSim: Differentiable Rigid-Body Dynamics With Implicit Shapes—0
PAPooling: Graph-based Position Adaptive Aggregation of Local Geometry in Point Clouds—0
Not All Relations are Equal: Mining Informative Labels for Scene Graph Generation—0
Joint stereo 3D object detection and implicit surface reconstructionCode0
Panoptic Segmentation Meets Remote Sensing—0
Talk-to-Resolve: Combining scene understanding and spatial dialogue to resolve granular task ambiguity for a collocated robot—0
Robust 3D Scene Segmentation through Hierarchical and Learnable Part-Fusion—0
Robust deep learning-based semantic organ segmentation in hyperspectral images—0
DriveGuard: Robustification of Automated Driving Systems with Deep Spatio-Temporal Convolutional Autoencoder—0
When Neural Networks Using Different Sensors Create Similar Features—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