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 1081–1090 of 1723 papers

TitleStatusHype
Generalized 3D Self-supervised Learning Framework via Prompted Foreground-Aware Feature Contrast—0
Camera-Radar Perception for Autonomous Vehicles and ADAS: Concepts, Datasets and Metrics—0
CLIP-FO3D: Learning Free Open-world 3D Scene Representations from 2D Dense CLIP—0
VTQA: Visual Text Question Answering via Entity Alignment and Cross-Media ReasoningCode0
Unified Perception: Efficient Depth-Aware Video Panoptic Segmentation with Minimal Annotation Costs—0
APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation—0
Weakly-supervised HOI Detection via Prior-guided Bi-level Representation Learning—0
Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors—0
RemoteNet: Remote Sensing Image Segmentation Network based on Global-Local Information—0
Open Challenges for Monocular Single-shot 6D Object Pose Estimation—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