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 1161–1170 of 1723 papers

TitleStatusHype
On Efficient Real-Time Semantic Segmentation: A Survey—0
Waymo Open Dataset: Panoramic Video Panoptic Segmentation—0
A Multi-purpose Realistic Haze Benchmark with Quantifiable Haze Levels and Ground Truth—0
Unsupervised Foggy Scene Understanding via Self Spatial-Temporal Label DiffusionCode0
Extracting Zero-shot Common Sense from Large Language Models for Robot 3D Scene Understanding—0
Beyond RGB: Scene-Property Synthesis with Neural Radiance Fields—0
Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans—0
A Memory System of a Robot Cognitive Architecture and its Implementation in ArmarX—0
Towards Improving the Generation Quality of Autoregressive Slot VAEsCode0
SAMPLE-HD: Simultaneous Action and Motion Planning Learning Environment—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