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 1201–1210 of 1723 papers

TitleStatusHype
Unsupervised Single-shot Depth Estimation using Perceptual ReconstructionCode0
Moving Beyond Navigation with Active Neural SLAM—0
Towards holistic scene understanding: Semantic segmentation and beyond—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
Scene Graph Generation: A Comprehensive Survey—0
Glass Segmentation Using Intensity and Spectral Polarization Cues—0
Segment-Fusion: Hierarchical Context Fusion for Robust 3D Semantic Segmentation—0
Weakly Supervised Segmentation on Outdoor 4D Point Clouds With Temporal Matching and Spatial Graph PropagationCode0
HSPACE: Synthetic Parametric Humans Animated in Complex Environments—0
Distillation of Human-Object Interaction Contexts for Action Recognition—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