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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 411–420 of 1723 papers

TitleStatusHype
OFFSEG: A Semantic Segmentation Framework For Off-Road DrivingCode1
M3D-RPN: Monocular 3D Region Proposal Network for Object DetectionCode1
DI-V2X: Learning Domain-Invariant Representation for Vehicle-Infrastructure Collaborative 3D Object DetectionCode1
Mask4D: End-to-End Mask-Based 4D Panoptic Segmentation for LiDAR SequencesCode1
DPF: Learning Dense Prediction Fields with Weak SupervisionCode1
Boosting Omnidirectional Stereo Matching with a Pre-trained Depth Foundation ModelCode1
Bootstraping Clustering of Gaussians for View-consistent 3D Scene UnderstandingCode1
MCTS with Refinement for Proposals Selection Games in Scene UnderstandingCode1
Dual-Hybrid Attention Network for Specular Highlight RemovalCode1
Learning Object-Centric Representations of Multi-Object Scenes from Multiple ViewsCode1
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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