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 241–250 of 1723 papers

TitleStatusHype
Embodied Scene Understanding for Vision Language Models via MetaVQA—0
3UR-LLM: An End-to-End Multimodal Large Language Model for 3D Scene UnderstandingCode1
Hierarchical Superpixel Segmentation via Structural Information TheoryCode0
Zero-Shot Scene Understanding for Automatic Target Recognition Using Large Vision-Language Models—0
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving—0
Self-Supervised Partial Cycle-Consistency for Multi-View MatchingCode0
UniQ: Unified Decoder with Task-specific Queries for Efficient Scene Graph Generation—0
Vision-Language Models for Autonomous Driving: CLIP-Based Dynamic Scene Understanding—0
A Systematic Literature Review on Deep Learning-based Depth Estimation in Computer Vision—0
NextStop: An Improved Tracker For Panoptic LIDAR Segmentation DataCode0
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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