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 1061–1070 of 1723 papers

TitleStatusHype
Living in a Material World: Learning Material Properties from Full-Waveform Flash Lidar Data for Semantic Segmentation—0
Learning-based Relational Object Matching Across Views—0
ArK: Augmented Reality with Knowledge Interactive Emergent Ability—0
Neural Implicit Dense Semantic SLAM—0
Compositional 3D Human-Object Neural Animation—0
ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding—0
Factored Neural Representation for Scene Understanding—0
360^ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer—0
Semantic Segmentation with High Inference Speed in Off-Road EnvironmentsCode0
Video-kMaX: A Simple Unified Approach for Online and Near-Online Video Panoptic Segmentation—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