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 1371–1380 of 1723 papers

TitleStatusHype
What Can I Do Around Here? Deep Functional Scene Understanding for Cognitive Robots—0
What Demands Attention in Urban Street Scenes? From Scene Understanding towards Road Safety: A Survey of Vision-driven Datasets and Studies—0
What do We Learn by Semantic Scene Understanding for Remote Sensing imagery in CNN framework?—0
When Neural Networks Using Different Sensors Create Similar Features—0
When Visual Grounding Meets Gigapixel-level Large-scale Scenes: Benchmark and Approach—0
Why my photos look sideways or upside down? Detecting Canonical Orientation of Images using Convolutional Neural Networks—0
Wireless Sensing With Deep Spectrogram Network and Primitive Based Autoregressive Hybrid Channel Model—0
YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks—0
You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objects—0
You Only Speak Once to See—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