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 1381–1390 of 1723 papers

TitleStatusHype
Zero-Shot 4D Lidar Panoptic Segmentation—0
Zero-Shot Open-Vocabulary Tracking with Large Pre-Trained Models—0
Zero-Shot Scene Understanding for Automatic Target Recognition Using Large Vision-Language Models—0
Zero-Shot Semantic Segmentation via Spatial and Multi-Scale Aware Visual Class Embedding—0
ZRG: A Dataset for Multimodal 3D Residential Rooftop Understanding—0
Polarimetric Spatio-Temporal Light Transport Probing—0
Pop-up SLAM: Semantic Monocular Plane SLAM for Low-texture Environments—0
PoSeg: Pose-Aware Refinement Network for Human Instance Segmentation—0
PPTFormer: Pseudo Multi-Perspective Transformer for UAV Segmentation—0
Practical Auto-Calibration for Spatial Scene-Understanding from Crowdsourced Dashcamera Videos—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