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 221–230 of 1723 papers

TitleStatusHype
sshELF: Single-Shot Hierarchical Extrapolation of Latent Features for 3D Reconstruction from Sparse-Views—0
Mosaic3D: Foundation Dataset and Model for Open-Vocabulary 3D Segmentation—0
Event-aided Semantic Scene CompletionCode1
AquaticCLIP: A Vision-Language Foundation Model for Underwater Scene Analysis—0
Integrating LMM Planners and 3D Skill Policies for Generalizable Manipulation—0
Efficient Interactive 3D Multi-Object Removal—0
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding—0
PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding—0
Unveiling the Potential of iMarkers: Invisible Fiducial Markers for Advanced Robotics—0
HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and GenerationCode3
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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