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 391–400 of 1723 papers

TitleStatusHype
Dynamic Graph Message Passing Networks for Visual RecognitionCode1
Bi-level Dynamic Learning for Jointly Multi-modality Image Fusion and BeyondCode1
DPF: Learning Dense Prediction Fields with Weak SupervisionCode1
LiON: Learning Point-wise Abstaining Penalty for LiDAR Outlier DetectioN Using Diverse Synthetic DataCode1
No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen RepresentationsCode1
Digging Into Self-Supervised Monocular Depth EstimationCode1
Object Pose Estimation via the Aggregation of Diffusion FeaturesCode1
Learning to Tune Like an Expert: Interpretable and Scene-Aware Navigation via MLLM Reasoning and CVAE-Based AdaptationCode1
Bird's-Eye-View Panoptic Segmentation Using Monocular Frontal View ImagesCode1
Cityscapes-Panoptic-Parts and PASCAL-Panoptic-Parts datasets for Scene UnderstandingCode1
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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