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 181–190 of 1723 papers

TitleStatusHype
PyTorchGeoNodes: Enabling Differentiable Shape Programs for 3D Shape ReconstructionCode1
GOV-NeSF: Generalizable Open-Vocabulary Neural Semantic FieldsCode1
Improving Visual Recognition with Hyperbolical Visual Hierarchy MappingCode1
VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object DetectionCode1
Object Pose Estimation via the Aggregation of Diffusion FeaturesCode1
AutoInst: Automatic Instance-Based Segmentation of LiDAR 3D ScansCode1
What if...?: Thinking Counterfactual Keywords Helps to Mitigate Hallucination in Large Multi-modal ModelsCode1
GroupContrast: Semantic-aware Self-supervised Representation Learning for 3D UnderstandingCode1
Optimizing Latent Graph Representations of Surgical Scenes for Zero-Shot Domain TransferCode1
Stealing Stable Diffusion Prior for Robust Monocular Depth EstimationCode1
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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