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 1251–1260 of 1723 papers

TitleStatusHype
Real-time Semantic Segmentation with Context Aggregation Network—0
BYE: Build Your Encoder with One Sequence of Exploration Data for Long-Term Dynamic Scene Understanding—0
RS-RAG: Bridging Remote Sensing Imagery and Comprehensive Knowledge with a Multi-Modal Dataset and Retrieval-Augmented Generation Model—0
BUTLER: Building Understanding in TextWorld via Language for Embodied Reasoning—0
Building an Affordances Map with Interactive Perception—0
Visual Jenga: Discovering Object Dependencies via Counterfactual Inpainting—0
S^3M-Net: Joint Learning of Semantic Segmentation and Stereo Matching for Autonomous Driving—0
S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-shot Segmentation—0
S4C: Self-Supervised Semantic Scene Completion with Neural Fields—0
Bridging Scene Understanding and Task Execution with Flexible Simulation Environments—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