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 1301–1310 of 1723 papers

TitleStatusHype
Multimodal Scale Consistency and Awareness for Monocular Self-Supervised Depth EstimationCode0
Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation—0
A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images—0
Audiovisual Highlight Detection in Videos—0
Bidirectional Multi-scale Attention Networks for Semantic Segmentation of Oblique UAV ImageryCode0
Optical flow and scene flow estimation: A survey—0
Deep Learning--Based Scene Simplification for Bionic VisionCode0
The Ikshana Hypothesis of Human Scene UnderstandingCode0
Rethinking Semantic Segmentation Evaluation for Explainability and Model Selection—0
SOSD-Net: Joint Semantic Object Segmentation and Depth Estimation from Monocular images—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