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 1131–1140 of 1723 papers

TitleStatusHype
PlaneSegNet: Fast and Robust Plane Estimation Using a Single-stage Instance Segmentation CNN—0
3D Vision-Language Gaussian Splatting—0
Plausible Uncertainties for Human Pose Regression—0
PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples—0
CodeMapping: Real-Time Dense Mapping for Sparse SLAM using Compact Scene Representations—0
Co-AttenDWG: Co-Attentive Dimension-Wise Gating and Expert Fusion for Multi-Modal Offensive Content Detection—0
ClusterVO: Clustering Moving Instances and Estimating Visual Odometry for Self and Surroundings—0
CloudFort: Enhancing Robustness of 3D Point Cloud Classification Against Backdoor Attacks via Spatial Partitioning and Ensemble Prediction—0
Cloud-Device Collaborative Learning for Multimodal Large Language Models—0
Clock-Modeled Ternary Spatial Relations for Visual Scene Analysis—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