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 1211–1220 of 1723 papers

TitleStatusHype
Improving Human-Object Interaction Detection via Phrase Learning and Label Composition—0
Image-to-Height Domain Translation for Synthetic Aperture Sonar—0
3D Scene Understanding at Urban Intersection using Stereo Vision and Digital Map—0
Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms—0
4DContrast: Contrastive Learning with Dynamic Correspondences for 3D Scene Understanding—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR ScansCode0
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision—0
Both Style and Fog Matter: Cumulative Domain Adaptation for Semantic Foggy Scene Understanding—0
Zero-Shot Semantic Segmentation via Spatial and Multi-Scale Aware Visual Class Embedding—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